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Let’s start with the “why.” What inspired Silicon Foundry to create Corporate Venture Capital (CVC) offering?

CVC is a very natural part of our business and what we do, right? We work with clients who are looking for innovative solutions to business problems, and we help them leverage technology from emerging companies to solve those challenges. When a corporate engages with a startup, there’s a wide range of potential outcomes. We think of it as a continuum. More often than not, it starts on the left side. That’s what we call venture clienting. In that scenario, the startup becomes a vendor. The corporate learns about a promising company and then adopts its product or service within their business. It’s a commercial relationship.

On the far right of the spectrum, you have M&A. That’s when the solution is so critical that the corporate decides they need to own it outright. At that point, it becomes a build-versus-buy decision. In between those two ends of the spectrum, you’ve got everything from simple partnerships or joint ventures, which may or may not involve any economics, to strategic investments. These aren’t full acquisitions, but they reflect a belief that supporting the startup is aligned with the corporate’s long-term interests. Maybe the corporate becomes a major customer, which in turn helps the startup raise its next round. That alignment is beneficial to both sides.

Then you get into questions like: Is investment part of the corporate’s standard operating procedure, or do they need to create a specific vehicle to do it? Over time, we’ve seen more corporates institutionalize their investment programs, not just investing opportunistically in helpful companies, but actively seeking them out and supporting them through formal processes.

That means doing the same upfront work, scouting, diligence, founder interactions, and economic evaluation, as they would in venture clienting. The only difference is the outcome. Whether they’re forming a commercial partnership or making an equity investment, the motions are the same. It’s muscle memory at this point.

Why do you believe CVC is particularly relevant right now?

One of the things we’ve consistently found, especially in corporate development, is that these areas are significantly understaffed. A common path for a corporate to establish a CVC is that, somewhere along the way, they’ve made a handful of investments, often tied to partnerships, but without a clear process or structure. Eventually, they come to the realization that a defined investment strategy could align closely with their broader strategic goals.

But you can’t just press a button and have a functioning CVC. Typically, someone from corporate development, M&A, or investments steps in to take on that responsibility. More often than not, though, they don’t have true venture capital experience. These are small teams to begin with, and that experience gap is real.

That’s where we come in. We essentially plug in and provide the infrastructure, access, and expertise they need. Because you can’t just hang out a shingle and say, “We’re a CVC now,” and expect startups to line up. You have to build visibility. You have to be a compelling storyteller. And again, that’s where we add value. We integrate directly into these under-resourced or under-prepared teams and accelerate their time to value doing everything except, in most cases, actually writing the check.

In your own words, how would you explain the impact this offering has for corporate leaders?

I think it’s huge. Imagine the scenario I just described. You’ve got one corporate development person at a legacy company in the Midwest who now suddenly holds the title “Head of XYZ Ventures.” There isn’t really a playbook for him. That’s why the timing and opportunity here are so important. From a CEO’s perspective, it all comes down to time to value. That new investment professional or team might take six months or more to get their sea legs. We can have them up and running almost instantly, starting a real program right away.

I’m working with a client right now in that exact situation. They see the value in being able to skip the long setup process. Instead of hiring a whole team or figuring out the structure and best practices from scratch, they’re essentially getting a full CVC capability out of the box.

And that creates real value, especially from the top down.

What’s a misconception people often have about this offering?

Sometimes the outside world, prospects more than clients, misunderstands what we do. One of the biggest misconceptions is that we’re an investor. I can’t tell you how many messages I get from startups saying, “Hey, we’re raising a round. Does Silicon Foundry want to participate?”

That’s a common misperception.

There are others, too, and we’ve got good answers for all of them. In some cases, not just in the CVC space but across many of our offerings, corporates wonder what our angle is. Because we have strong relationships with both VCs and startups, they sometimes ask: Do we have skin in the game? Are we financially tied to the startups we introduce?

We’ve had situations, without naming names, where members of a client team were concerned that the startups we were recommending might be companies we had invested in or were somehow getting paid by. The concern was, how could they trust that we were showing them the right companies, not just companies we had a vested interest in?

That kind of skepticism sometimes carries over into the CVC conversation as well. “Are you pushing these startups because you want deals to happen, or because they’re truly the best fit for us?” The answer is simple. Just like with everything else we do, our work is fixed fee. We don’t get paid per deal. That means we’re not incentivized to get any deal done. We’re incentivized to help get the right deals done. Our model is uniquely aligned with our clients. That’s the whole point.

Can you share a favorite anecdote or example where this offering really made a difference for a client?

I’m actually working on one right now that’s a great example, and it cuts both ways.

This is a corporate that decided to set up a CVC. They’ve got a strong strategy and corporate development lead driving it, but that’s essentially the entire team. Within just a few months, we’ve become his trusted advisor—his thought partner.

He’ll come back from meetings and immediately email us saying, “Hey, I just saw this really interesting company. Let’s get something set up. I want you to meet them.” It honestly reminds me of my VC days, when I’d meet a compelling startup and pick up the phone to call one of my partners right away. It’s been great to see how quickly we’ve become embedded in their process.

What’s even more interesting is that in one case, we were essentially being paid to tell him not to do a deal he was excited about. He was nearly ready to move to a term sheet. But our diligence surfaced a major red flag and something we felt had to be addressed before moving forward. At first, I don’t think he or the company saw it the way we did. But once we walked them through it from our perspective, they came around. They realized they couldn’t go forward with the deal.

Helping clients avoid costly mistakes can be just as valuable, sometimes even more so, than helping them find the next big thing.

What’s something you personally learned or found surprising while building or delivering the CVC offering?

This shouldn’t have been surprising, I guess, but I found it surprising how quickly I realized how much I enjoy being on the venture side. You’re a lot closer to the playing field and really get to flex those muscles. That’s been a nice surprise.

The other surprise, and maybe it shouldn’t be, since it’s what I’m selling, is how easy it’s been to gain traction with other investors and startups when using the Foundry calling card on behalf of [X CVC]. I thought we might get more pushback, or run into the usual complaints that VCs and startups have about corporates, things like slow timelines, complicated processes, or just being more trouble than they’re worth.

But I’ve found that we’re actually able to grease the skids a bit. We help open doors more quickly because we speak “founder,” and that makes it really natural for us to play that middle role. We can go back to the founder and explain what we heard from our client in a way that makes sense to a startup, and we can return to the client with the founder’s message, framed appropriately for a corporate audience. There’s a real translation role there, and I could go on and on about it.

If you could give one piece of advice to a corporate leader considering this offering, what would it be?

I’m a big believer in corporate venture capital. I think it’s an important tool in the toolkit for any strategy or corporate development professional. Being able to make investments that are aligned with your strategic interests is incredibly valuable, and that alignment, in my view, is essential. Sometimes corporates forget that. But when an investment is truly aligned with the company’s broader objectives, it can be incredibly powerful. Even if you’re not looking for a direct ROI from every deal—and of course, CVCs should be thinking about ROI alongside strategic value—that alignment makes the investment meaningful.

That’s why having a third-party expert who can act as an extension of your team is so important. In a nutshell, that’s what we offer. It’s like the saying, “Don’t try this at home” or maybe more accurately, “Don’t try this at home just yet.”

We don’t have to be a permanent fixture. Honestly, what would make me happiest is helping to instill some of that institutional knowledge in the client’s team, imparting the DNA, so to speak. Not fishing for them, but teaching them how to fish. It’s about helping them build their own best practices so they can eventually take the training wheels off. I’m oversimplifying, but that’s a big part of this role, empowering the team so they eventually don’t need Silicon Foundry.

And that’s exactly why it makes sense. Unless you already have an experienced investor stepping into the role, why wouldn’t you bring in this kind of support?

What excites you most about working in this space?

In many ways, it’s the same thing that excites me about all the work we do. It’s about helping clients solve really interesting problems and doing it in a space I care deeply about, which is the startup ecosystem and technology. Broadly speaking, just about everything we do at Silicon Foundry excites me for that reason. But what really energizes me in this category is the chance to take nearly 20 years of venture capital experience and put it to work for our corporate clients. It’s incredibly rewarding to channel that knowledge, network, and know-how like a firehose into a corporate setting and help them solve complex challenges and uncover new opportunities.

Venture capital has always been known as an apprenticeship business. You learn from those who came before you, then try to follow in their footsteps. Mentorship has always been a big part of that. And in this work, we get to play that same role, mentoring the next generation of corporate venture capital leaders and sharing whatever wisdom we’ve gathered along the way.

Anyone who knows us knows that mentorship, teaching, and best practices are a huge part of our culture. For us, this work is a major form of giving back.

And I should emphasize, this isn’t just about me. I’ve talked a bit about my background, but I’m not unique in this regard. Neal has tremendous venture experience. Eric has venture experience. Several of our other partners and junior team members do, too. It’s not just one or two of us.

Even if I’m not directly staffed on a project, our clients still benefit from our collective experience. We’re a small, highly collaborative team. If my name’s not on the report, I’m still there behind the scenes, supporting my partners and contributing to the work.

The post Inside Silicon Foundry: Managing Director Mark Menell on Building and Evolving Corporate Venture Capital Programs appeared first on Silicon Foundry.

The advisory firm scaled enterprise AI execution capabilities, expanded its European and Asian presences, and intensified its Piloting, CVC, and M&A offerings to Members. 

SAN FRANCISCO, CA — Silicon Foundry, a Kearney company, marked 2025 as a pivotal year in its evolution, moving decisively from innovation advisory into hands-on execution as enterprises accelerated the deployment of artificial intelligence and venture-driven growth initiatives. Over the past year, the firm expanded its global footprint, deepened its enterprise AI execution capabilities, and broadened its innovation offerings to support clients not just in identifying opportunity but in piloting, scaling, and delivering measurable outcomes.

As corporations moved beyond AI experimentation toward structured pilots, agentic solutions, and enterprise-wide deployments, Silicon Foundry emerged as a trusted execution partner to over 50 multinational corporations, governments, and private market investors. With two-thirds of its business now driven by clients outside the United States, the firm scaled its global team and execution platforms across AI, corporate venture capital, pilot studios, and M&A to meet rising demand for disciplined, outcome-driven innovation.

“This has been a breakthrough year in every sense,” said Neal Hansch, CEO of Silicon Foundry. “We expanded the global coverage of our professionals and ecosystems we’re deeply embedded in, broadened the ways in which we support the innovation agendas of our Members, and scaled the execution of outcomes across our offerings. The momentum we built over the last year is representative, durable, and, as expected, has continued to accelerate into the first quarter of 2026.”

Dominance of Artificial Intelligence

Across all industries, enterprise AI and the exploration/adoption of agentic solutions emerged as the single strongest demand driver over 2025 and into 2026. Universally, corporations increasingly sought understanding of the true ‘state of play’ – eager to separate hype from reality – and an unbiased view on the crowded landscape of emerging AI platforms and capabilities. With a sense of urgency balanced with justifiable caution, leaders are anxious to selectively leverage AI to enhance operational efficiencies and unlock new opportunities for their businesses. 

At the same time, these leaders are seeking clarity on how to gauge enterprise readiness, navigate endless vendor noise, and decide between the available buy-build-partner options that exist today. Headquartered in Silicon Valley, the undeniable epicenter of the AI revolution and home to nearly two-thirds of all AI-related venture capital funding, SiF has further solidified its role over the past year as an independent, trusted advisor to C-suite leaders navigating these challenges and opportunities. Enterprises increasingly turned to SiF for systematic, comprehensive support and structured pathways to identify, evaluate, pilot, and scale the rollout of, investment into, or acquisition of relevant emerging technologies. 

Expansion Across Europe & Asia

While SiF has served a wide range of corporations hailing from across Europe and Asia since its inception over a decade ago, it was a milestone year for the firm as it established direct presence with team members today on the ground in Germany, France, and Japan. This expansion fulfills the firm’s previously announced growth plans and reflects increasing enterprise demand for structured, execution-driven innovation programs that bridge major innovation ecosystems. Similarly, in the Middle East, SiF’s footprint and impact have broadened in recent quarters to support the design and operation of Innovation Hub programs and accelerators in the UAE, Qatar, and Saudi Arabia. 

In addition to growing its roster of full-time talent, SiF actively added to its Venture Partner program, comprised of seasoned industry leaders who have spent decades building companies, shaping markets, and leading complex transformations inside F1000 enterprises. These extended colleagues bring an additional layer of depth to SiF’s work, expanding the firm’s deep networks, contributing targeted industry expertise, and helping SiF provide its Members with unique and proprietary, real-time insights.           

From Advisory to Execution

Across the enterprise landscape in 2025, corporate leadership teams sharpened their focus on disciplined venture execution, operating efficiency, and scalable innovation models. As organizations moved beyond strategy and sensing toward real deployment, SiF accelerated its evolution from trusted advisor to hands-on execution partner. This shift has been most visible across SiF’s Corporate Venture Capital, Pilot Studio, and Corporate Development as a Service (CDaaS) offerings, leading Members to turn to SiF to help launch and operate the mechanisms required to turn innovation into measurable business impact.

Corporate Venture Capital teams, in particular, sought operating structures that would allow them to move faster, focus scarce internal resources, and deliver clearer outcomes from strategic capital deployment. Today, SiF supports more than 15 corporate venture programs collectively managing over $1 billion in strategic capital, working side by side with internal teams to tighten fund thesis, source opportunities, diligence targets, structure investments, and activate partnerships that extend well beyond the check. With more than 3,000 corporations investing in startups last year and one in five startup funding rounds now including a corporate backer, the need for disciplined execution, governance, and integration has never been higher.

In parallel, SiF formally launched two execution oriented services to meet rising enterprise demand. Pilot Studio, a joint Silicon Foundry and Kearney offering, was designed to bridge the persistent gap between innovation strategy and implementation by enabling rapid, high-impact pilots with emerging AI and technology startups. Built to move beyond innovation theater, Pilot Studio provides a structured, repeatable model that helps enterprises identify priority use cases, source and vet startups globally, launch pilots, track outcomes, and prepare the organization for scale. Early engagements have helped clients compress AI ideation to adoption timelines from years to months while creating clear pathways to enterprise deployment.

Alongside Pilot Studio, SiF expanded its Corporate Development as a Service (CDaaS) offering to support corporate development and strategy teams that are under pressure to execute growth initiatives without expanding permanent headcount. Acting as a true extension of internal teams, CDaaS supports the full lifecycle from market landscapes and acquisition theses through diligence and deal execution, allowing clients to pursue inorganic growth opportunities with greater speed and confidence.

Experiences & Executive Treks

When the right mix of visionary leaders, bold thinkers, and diverse perspectives comes together in the same room, game-changing ideas take shape. Experiences, curated events by SiF, are a core component of our offerings to Members and how the firm physically convenes its global network. Every year, SiF develops a slate of intimate, high-impact gatherings where forward-thinking executives, founders, investors, and thought leaders can connect, exchange ideas, and uncover opportunities to spark candid dialogue and explore transformative trends redefining business. Last year, SiF delivered a robust slate of experiential programming, hosting more than 40 invite-only events across the globe, spanning topical interactive roundtable discussions to intimate satellite events held in parallel to bellwether annual industry conferences around the world, including CERAWeek, CES, FII, GCVI, HumanX, Manifest, NRF, MWC, JP Morgan Healthcare conference, etc. 

In addition to these events for its community, SiF’s team conducted over 25 private Executive Treks over the past year for its Members and clients of Kearney. Ranging from condensed half-day experiences to multi-day regional immersions designed to widen perspectives into the art of the possible. These innovation-focused experiences were hosted in San Francisco, New York City, Frisco, Los Angeles, and London, among other destinations. Key trends addressed, and representative themes of these treks included:

• Intelligent Enterprise: Unlocking Growth Through Agents + Applied AI
• CPG Next: Consumer Signals and Innovation Shaping What’s Ahead
• Growth Horizons: Corporate Expansion and Emerging Innovation Hubs
• Financial Services Reinvented: Leadership and Technology Transformation
• Procurement Elevated: AI Skills for a Smarter Supply Chain
• From Product to Shelf: Inventory Intelligence Powering Modern Commerce

Intended not just to inspire but lead to action, these executive treks often take place in the context of upcoming or already underway digital transformation initiatives. In collaboration with Kearney, a major retailer Member progressed from a series of brief immersion treks into an expanded Pilot Studio engagement within the consumer sector, underscoring how treks are increasingly serving as a gateway to full-scale innovation execution programs.

The Collectives as Strategic Connective Layer

Launched just over a year ago, The Collectives membership program serves as a critical connective layer for insights gathering, peer-to-peer knowledge sharing, curated relationship building, and a stage set to empower enterprise collaborations. This past fall, SiF and Kearney convened a select group of two dozen C-suite operators, entrepreneurs, and venture investors in Amsterdam for the inaugural Assembly of the TC// Energy + Utilities Collective. Key themes across the multi-day gathering focused on collaborative approaches to grid modernization, decarbonization, and infrastructure resilience. Attending companies represented 15 countries and hundreds of billions of dollars in market capitalizations, annual revenues, and budgeted spending. SiF is excited to announce that the next Assembly of this Collective is scheduled to take place in Boston, adjacent to the MIT campus, later this spring.

Silicon Foundry’s Outlook For 2026

As enterprise innovation moves decisively from exploration to execution and measurable ROI, SiF enters 2026 with clarity and momentum. The global innovation landscape is tightening around delivery, and the data reinforces that shift. 

Corporate venture capital is at an all-time high. Corporate participation in startup funding continues to expand, marking a 29% increase in the number of active corporate investors year-over-year, as they seek strategic access to emerging technologies, AI capabilities, and new growth vectors.  At the same time, enterprise priorities are shifting toward execution. After several years of AI experimentation, leaders are demanding proof points, production deployments, and business cases that stand up to scrutiny. Recent CIO and IT leader surveys show 60% of companies now using AI in active production (up from 39% the year prior), while 90% plan to increase AI spending in 2026, with many allocating dedicated AI budgets. The message is clear: AI has moved from experimentation to core infrastructure.

M&A activity is expected to remain strong into 2026, driven less by consolidation and more by capability acquisition. Morgan Stanley reports global M&A volume rose approximately 40% in 2025, fueled by large transactions, and expects momentum to continue as Fortune 1000 companies pursue AI, software, and technology-enabled capabilities. Despite ongoing geopolitical and macro uncertainty, Silicon Foundry believes AI adoption across enterprises and consumers will continue to accelerate, driven by sustained pressure to unlock productivity, differentiate competitively, and modernize operating models. Markets in early 2026 are signaling a clear pivot toward execution discipline, including governance, integration, data readiness, and ROI measurement.

Silicon Foundry is well-positioned for this moment. As Members demand faster pathways from strategy to outcomes, SiF’s execution offerings are designed to help enterprises move from opportunity identification to pilots, partnerships, acquisitions, and scaled adoption with measurable business impact.

Silicon Foundry’s top priorities for 2026 include:

• Formalizing its European operations and expanding regional enterprise engagement
• Scaling its CVC advisory and CDaaS programs
• Continuing to support corporations in defining AI strategy and deploying real-world pilots
  

“We entered 2026 with clarity, scale, and continued momentum,” said Neal Hansch, CEO of Silicon Foundry. “Our next phase is about institutionalizing what we’ve built, globally expanding our operating model, strengthening how enterprises execute through CVC, and continuing to move innovation from strategy into real, measurable business outcomes.”

ABOUT SILICON FOUNDRY:

Silicon Foundry, a Kearney company, is an innovation advisory firm that catalyzes opportunities and accelerates change to push the frontier of what’s possible. The firm helps its Members navigate new technologies and market shifts, discover and engage with key emerging leaders, and unlock high-impact customer, partnership, investment, co-creation, and acquisition opportunities. Our Members include a diverse set of the world’s leading multinational corporations across a wide range of industries, from entertainment to retail, telecom to transportation, oil & gas to mining, chemicals to cosmetics, sovereign wealth and economic development organizations, and many more. Learn more at www.sifoundry.com.

ABOUT KEARNEY:

Kearney is a leading global management consulting firm. For nearly 100 years, Kearney has been a trusted advisor to C-suites, government bodies, and nonprofit organizations. Driven to be the difference between a big idea and making it happen, the firm works alongside its clients to regenerate their businesses and create a future that works for everyone. Learn more at: www.kearney.com. 

The post A Year in Acceleration: Silicon Foundry Advances Enterprise AI and Global Innovation in 2025 appeared first on Silicon Foundry.

Venture ecosystems reveal architectural shifts years before the data. Is your organization positioned to see them?

Your strategic planning process is probably quite good at answering the wrong question.

It tracks market share in categories that are being redrawn. It monitors competitors, optimizing for an architecture that’s becoming less relevant. It produces forecasts that are defensible in board presentations and useless for detecting the transition actually underway.

But the failure isn’t intellectual. It’s structural. Planning systems are built to detect competitive motion, such as product launches, pricing moves, and share shifts. They are not built to detect architectural motion when the category boundaries themselves are moving. Competitive motion is loud; it generates the data strategy teams are trained to watch. On the other hand, by the time architectural motion shows up in market share reports, the underlying transfer of power has already happened.

The question is where architectural motion becomes visible first. The answer, consistently, is the venture ecosystem.

When Control Moved Beneath the Surface

Between 2005 and 2020, hyperscaler server procurement inverted—from roughly 80% branded OEMs to roughly 80% ODM and self-designed systems. Dell, HPE, and Lenovo didn’t forget how to build servers. The architecture of control changed underneath them.

Disaggregation, software-defined infrastructure, and customer-defined specifications transferred leverage from suppliers to buyers who could define the system. The ODM channel became a capability rather than a competitor. The vendors who once controlled the stack found themselves competing on execution in a segment where differentiation was narrowing, and margins were compressing.

In 2014, if you wanted to understand where this was heading, you could read Gartner reports showing Dell and HPE leading the server market. Or you could look at what was getting funded: software-defined infrastructure, composable systems, hyperscaler-adjacent services. The Gartner data was accurate in 2014. The venture activity was predictive of 2020.

By the time market share reports reflected the shift, the window for strategic adaptation had largely closed. The companies that repositioned early had seen the signal in the ecosystem years before it appeared in the data.

Networking Is Following the Same Path

Networking is now undergoing a similar transition. The underlying driver is different: the network is no longer treated as a component that connects to the server, but is increasingly treated as part of the compute itself. When that happens, the category stops behaving like “networking” and starts acting like systems architecture.

AI accelerates this because it punishes siloed optimization. In classic enterprise infrastructure, it was defensible to separate “compute” decisions and “network” decisions, evaluate each against its own benchmarks, and allocate capital accordingly. In large-scale AI training and inference, performance and cost are end-to-end properties. Latency, bandwidth, topology, congestion control, workload placement—these interact in ways that don’t respect the org chart.

Organizations still treating network and server as separable categories aren’t making forecast errors. They’re making category errors, allocating against labels that no longer describe how value is created.

The signals are visible now. Hyperscalers are designing their own switches and routing production through ODMs. Venture capital is flowing into network operating systems, programmable data planes, and fabric architectures designed for AI workloads. Multiple founders are independently building companies around the same “in-between” problems that don’t fit legacy categories.

What Breaks When You Miss Architectural Shifts

When architectural motion goes undetected, the failures cascade through executive systems. First, capital allocation breaks. Most companies fund the network and compute separately, optimizing each as if they were independent. In AI workloads, this misallocates capital, overfunding what fits legacy categories while starving the real system bottlenecks. You can spend more and still get less throughput. 

Next, M&A logic fails because M&A screening is built for stable categories, using filters like revenue quality, margins, and integration risk. That logic breaks for emerging architectures, which look wrong on standard metrics and don’t map cleanly to the org chart. They get dismissed as “not core to strategy,” when in reality they’re organized around what comes next, not what exists today.

Finally, decision velocity is the visible casualty. When accountability is separated along historical infrastructure lines, integrated architecture choices become cross-functional negotiations. That’s a polite description for what actually happens: consensus takes time, and time becomes an unforced error in a market where the architecture is moving quickly. They’ll shape the interfaces and operating norms that slower organizations eventually have to adopt. Furthermore, traditional planning inputs reinforce these failures. Market share data lags 12–18 months; competitive intelligence maps known players within known product definitions; vendor roadmaps anchor assumptions to incumbent architectures. In periods of architectural transition, this bias toward stability is fatal.

Lessons From Corporate Venture Capital

At Celestica, we deployed over $15 million through our venture program and evaluated hundreds of additional opportunities. The financial returns were fine. The strategic value was in what we learned about where the architecture was moving.

The most important insight was never which startups would become unicorns. It was which problems were attracting concentrated founder and investor attention before the market consensus recognized them as strategic. Those clusters were leading indicators of where control points were migrating.  When multiple teams independently decide the same low-visibility problem is worth years of their lives, that’s signal. When investors who were funding one layer of the stack shift their attention to a different layer, that’s also signal.

The startups were probes into the architecture. Their collective activity drew a map of where value was migrating—visible 18-24 months before it showed up in enterprise purchasing patterns or analyst reports. Early-stage companies because they cluster around emerging seams in the stack before the broader market recognizes them as strategic. 

When a founder raises capital to build a network operating system that abstracts hardware, or when multiple companies get funded to solve the same “in-between” problem that doesn’t fit legacy categories, that’s a signal the categories themselves are breaking. Whether the startup succeeds or not, focus on their activity and early customer traction reveal about which interfaces are becoming control points and which are becoming commodities.

Here’s three patterns worth tracking:

• Clustering around low-visibility infrastructure. When multiple founders independently start companies solving the same boring problem—observability, orchestration, data movement—something has shifted. That layer has become a bottleneck, and existing solutions aren’t adequate. The fact that it looks boring is part of why incumbents miss it.
• Customers paying before the category exists. Early enterprise adoption of startups that don’t fit procurement categories is a strong signal. The pain is acute enough that buyers are working around their own purchasing systems to solve it. That’s leading-indicator behavior.
• Investor thesis migration. What the best infrastructure investors funded three years ago versus today tells you which layers they believe are becoming strategic. They’re not always right, but they’re processing signals you’re probably not seeing.

Watch the ecosystem, and these patterns appear in real time. Rely on market data, and you see them 2–3 years late, the difference between shaping the architecture and reacting to it. The question executives need to ask themselves: do you have this map, or are you waiting for it to arrive in a format your planning process already knows how to read?

Turning Innovation Programs into Sensing Systems

Most large companies have venture arms, accelerators, or scouting functions—but most generate negligible strategic intelligence. The failure isn’t the people; it’s the design. Programs are often optimized for visibility, not insight. They track deal flow, investments, and portfolio valuations, rarely asking whether the intelligence influenced capital allocation, M&A screening, or architecture decisions. Even when insights emerge, they must cross organizational boundaries that weren’t built for them, and success is measured by deployment rather than pattern recognition. The result: companies spend real money on ecosystem access, generate insights, and fail to act.

Here’s how to do it differently:

• Invest in relationships, not deal flow. The most valuable sensing comes from ongoing interactions with founders, investors, and technical leaders—before signals are packaged into pitch decks or fundraises. Continuity and reciprocity are key.
  
• Be in the room early. Strategic intelligence is densest at seed and Series A—when founders decide what to build, early customers decide what to buy, and investors form theses about which layers matter. Waiting until growth stages is reading yesterday’s paper.
• Separate intelligence from investing. You don’t need a venture fund to sense the ecosystem. Systematic access and a process for extracting signal matter more than IRR. Measure programs by decision impact: did the intelligence change how capital or M&A decisions were made?
• Assign accountability. One person—not a committee—needs to own the question: “Which interfaces in our market are becoming strategic, and which are commoditizing?” They need direct ecosystem relationships and a mandate to report honestly.
• Build translation with teeth. Insight without action is theater. Define which decisions ecosystem intelligence should inform—architecture roadmaps, capital allocation, M&A screening, partnerships—and create auditable gates for integration.
• Force executive adoption. Sensing only matters if it reshapes decision frameworks. Detecting architectural shifts early requires that intelligence has a path into the decisions that truly matter.
  

Most companies have innovation programs. Few have real sensing systems.

The Cost of Waiting

In stable periods, you can afford to wait for signals to reach your dashboards. Market share data and analyst reports will arrive in time.

In transitions, they arrive too late.

The signals are visible in the venture ecosystem 2-4 years before they show up in the data your planning process was built to track. That window is when strategic options are open, and adaptation is cheap. After the window closes, you’re not adapting—you’re reacting, and the cost compounds.

Hyperscale networking is being redrawn right now, but the deeper point isn’t about networking. It’s that strategic advantage now depends less on how well you execute within known categories and more on how early you detect that the categories themselves are changing.

The insight lives in the ecosystem. What matters is whether you’re able to see it early, and whether your organization can respond before the ground shifts. No company is as entrenched as it believes, not because incumbents are careless, but because categories continue to evolve whether leaders are ready or not.

Alok K. Agrawal is the Managing Director and CEO of Agrawal Capital, LLC and a Venture Partner with Silicon Foundry. He has served as Chief Strategy Officer at three companies across multiple industries, and now advises and invests in early-stage ventures.

Copyright © 2026 Agrawal Capital, LLC. All rights reserved. This article is published by Kearney and Silicon Foundry under a non-exclusive license. Agrawal Capital, LLC retains all rights, including the right to reuse or republish this material elsewhere with attribution.

The post Why Market Leaders Miss AI Infrastructure Shifts appeared first on Silicon Foundry.

Founded by an exceptional team with backgrounds at Tesla, Rivian, Boeing, and Walmart, Mytra was built to address a persistent operational gap: while planning software and analytics have advanced rapidly, the physical movement of materials inside facilities has remained rigid, labor-intensive, and difficult to adapt as business needs change.  The company’s board includes the former CFO of Tesla, Zach Kirkhorn, adding deep financial and operational experience as Mytra scales across warehouse and manufacturing environments where uptime and flexibility are critical.

Now moving from pilot to production, Mytra has raised a $120 million in Series C led by Avenir Growth Capital and is working with Fortune 100 customers (incl. Albertsons), with its first enterprise rollout completed in early 2024.

Tanya Privé had the pleasure of sitting down with Chris to discuss next-generation warehouse and manufacturing infrastructure.

Press play to listen to the conversation

TANYA PRIVÉ: We’re pleased to welcome Chris Walti, Founder and CEO of Mytra. Chris, it’s a pleasure to have you here with us today.

CHRIS WALTI: Hi Tanya, thank you for having me!

TANYA: Let’s start from the beginning. You built Mytra with a team coming from Tesla, Rivian, Boeing, and Walmart. What experiences across those environments made it clear that material flow was the problem worth solving, and why did it require a fundamentally new approach?

CHRIS: The origin of Mytra really comes from this layered set of experiences. For my part, I spent those eight years at Tesla, and a big chunk of that was wrestling with the material flow system for the Model 3 general assembly line. It was a real tangle of legacy automation, including multiple disparate systems, a ton of single points of failure, and a structure that just wasn’t designed for the kind of flexibility and agility we needed. We spent months trying to fix it, and that really drove home that this wasn’t just a local Tesla problem. It was a fundamental industry issue.

In parallel, I also led the mobile robotics team and the humanoid program, building some of the most state-of-the-art robotics in the industry. And that gave me this dual perspective: on one hand, we had all this cutting-edge robotics capability; on the other, we were still struggling with the same old rigidity in material flow. And it became obvious that the solution wasn’t to add more complexity. It was to rethink the system entirely.

And this wasn’t just my realization. Our founding team brought in folks from Rivian, Walmart, and Boeing – all from different industries that faced the same challenge. They’d all seen that the industry wasn’t looking for more sci-fi robots or more complex automation. Instead, the big “aha” moment was that we needed to re-architect the system with simpler, more primitive building blocks that were software-driven and flexible.

In other words, I learned that the future of material flow isn’t about the fanciest robot; it’s about making the entire flow architecture fundamentally more adaptable. And that’s the core idea behind Mytra. We took all those lessons from different environments and realized that the industry needs a simpler, software-defined approach to stay flexible and resilient.

TANYA: You touched on something important there, which is the gap between advanced robotics and inflexible material flow. If that’s been clear for years, why has the industry struggled for so long to make material movement more adaptable, even with massive automation investment?

CHRIS: The core reason is that the industry just hasn’t had that systems-level rethink yet. If you look at sectors like automotive, aerospace, or even defense, they all had their own moments of transformation when someone came in and said, “We need to rethink this from the ground up.” But in material flow, a lot of the automation is still very customized, very one-off, and not productized. Every warehouse is a bit of a snowflake. And that means even within the same company, you might have different automation systems in different facilities, different PLCs, different actuators. It’s all incredibly fragmented.

The analogy I like to use is that it’s like the early days of computing. Everyone uses their devices differently, but the hardware is basically the same, and the flexibility comes from the software layer. In logistics and manufacturing, we haven’t reached that point yet. Designing simple, standardized systems is actually one of the hardest things to do, and it requires a new mindset.

So in short, material flow is still broken because the industry hasn’t had that big re-architecture moment yet. But that’s changing now. Just like Tesla rethought automotive, or SpaceX did for space, we’re bringing that same kind of systems thinking to logistics. And that’s what Mytra is all about: turning what used to be a snowflake problem into a standardized, software-driven solution that can finally adapt and scale.

TANYA: You’re now moving from pilots to production with Fortune 100 customers. What tends to break when next-generation automation meets live, high-throughput operations?

CHRIS: Well, if you look at the industry track record, even introducing a new WMS into a facility can take six to twelve months before it really hits its stride. The norm is that new technology doesn’t just work perfectly out of the box. What we’ve seen at Mytra is that you have to design for adaptability from day one. In our very first customer project, we didn’t just get the system up to the service level agreement quickly; within about a month and a half, we were exceeding that SLA by roughly three times the throughput. How? By making it all about software-driven flexibility. Instead of relying on hardware tweaks that can take weeks or months, we could identify an issue, push a software fix, and have it live the same day. That’s the agility that’s been missing.

Another big piece is bringing the people on the ground into the loop early. We spent a lot of time understanding the operators’ needs, listening to forklift drivers, and making sure they were part of the journey. It’s amazing how often new automation is designed in an ivory tower without talking to the actual users. We flipped that script, and that human-centric approach made a huge difference.

In the end, what tends to break is the assumption that you can plan for perfection from day one. You simply can’t. But you can design for rapid iteration, you can make software the backbone of flexibility, and you can treat the people on the floor as partners rather than afterthoughts. That’s how you get from pilot to production without everything falling apart.

TANYA: All of that sounds powerful in practice. When you’re in the room with executives considering Mytra, what usually lands hardest for them in the business case—labor savings, better use of space, throughput gains, or resilience?

CHRIS: When executives evaluate Mytra, they often come in looking for very tangible business cases. And if we’re honest, the two metrics that almost always underwrite the investment are labor efficiency and space utilization. In other words, can we do more with the same or less labor, and can we use our warehouse or factory space more effectively? Those are the clear ROI drivers everyone understands from day one.

But what we find is that Mytra isn’t just about being a point solution. We want to be the strategic partner that helps them build a flexible, resilient system of record for their automation. And over time, as they begin to see those labor and space benefits, they also start to realize the value of flexibility and resilience. At first, those can be harder for them to quantify. But once they see how quickly they can adapt to new demands, reconfigure flows, or scale up capacity without a huge new hardware project, that becomes a big part of the business case too.

In short, we lead with labor and space because that’s easy to measure. But over time, our customers start to see that the real magic is in having a system that can change as fast as they do. And that’s where Mytra really stands out.

TANYA: You emphasize a no-integration-code approach. In practice, where do large organizations still underestimate the operational change required?

CHRIS: So when it comes to integration and change management, we do emphasize that Mytra’s approach requires no custom integration code. That definitely reduces the friction on the IT side. But one of the big values of our system is that it also lowers the amount of human change management needed. In a traditional warehouse, if you introduce a new slotting approach or a new routing method, there’s a lag. People have to relearn the process, get used to new tasks, and that can slow things down.

With Mytra, because we modularize and simplify the human tasks, the change is a lot easier. We break down complex workflows into simpler building blocks. So if you know how to handle a case, you don’t have to master a whole new routing scheme suddenly. We’re basically making human tasks more consistent and less sensitive to operational changes. That means the workforce can adapt faster and with less disruption.

On the IT side, while we do remove a lot of the integration headaches, we’ve found that the real focus ends up being on security and compliance. Our customers’ logistics data is incredibly valuable and sensitive, so a lot of the deeper integration work is actually about making sure we meet all their security protocols and that the handoff is as frictionless as possible.

In short, the big surprise for large organizations is that while the tech integration is straightforward, the real win is that we reduce the human change burden too. By making human roles simpler and more modular, we make the whole transition smoother and faster. And that’s a huge part of the value we bring.

TANYA: If the system is doing more of the orchestration in software, what does that mean for the people on the floor day-to-day? How does a software-defined material flow system change its role?

CHRIS: So when we talk about how a software-defined material flow system changes the role of people on the warehouse or factory floor, one of the fundamental shifts is in reducing those physically grueling, injury-prone tasks. Having spent a lot of time in factories and warehouses, we know that material handling often leads to some of the toughest and most injury-prone jobs. Repetitive strain, heavy lifting, and constant maneuvering of loads can take a real toll on the human body.

What Mytra does is shift that dynamic. We take those zero-value-add tasks—just moving things from point A to point B—and we let the software and automation handle that. That frees up the human workers to focus on tasks that are less repetitive and physically punishing. Instead, they can handle more nuanced, dexterous, or higher-value tasks that require human judgment, creativity, and problem-solving.

In other words, we’re making the work more interesting and less about brute labor. It’s not just about efficiency; it’s also about making the workplace safer and more engaging. When you remove the heavy, repetitive strain and let humans do the things humans are best at, you not only reduce injuries, you also create a more fulfilling job environment. That’s a huge shift in the role of people on the floor, and it’s a big part of the value that a software-defined material flow system brings.

TANYA: Finally, five years from now, what about warehouse and manufacturing automation will feel obvious, but still isn’t widely understood today?

CHRIS: So if we think about five years from now, what’s going to feel obvious in warehouse and manufacturing automation, but maybe isn’t widely understood today, is just how much more efficient and dynamic the entire supply chain can become. Right now, we have a lot of waste, a lot of touches, and a lot of inefficiency built into logistics. The average product might go through half a dozen touch points before it gets to you, and there’s so much buffer inventory just sitting around. That’s GDP locked up in warehouses instead of being in the hands of consumers.

In the next five years, it’s going to become obvious that by putting software in the loop—by making each node in the supply chain smarter and more autonomous—we can cut down on that waste dramatically. We’ll start treating material flow a lot more like information flow on the internet—more agile, more flexible, and with far less waste and downtime.

And as we look even further out, maybe ten years, we’ll see things like autonomous trucking become the norm, and that’ll be a huge inflection point. Suddenly, the cost of moving smaller loads goes down, and logistics becomes more like a network of smaller, faster, more responsive nodes. Warehouses and factories that can adapt quickly will thrive in that environment.

In the end, what’ll feel obvious is that a software-defined supply chain isn’t just a nice-to-have; it’s the key to reducing waste, lowering costs, and making the whole system more sustainable and responsive. And that’s the future we’re excited to help build.

TANYA: Chris, thank you so much for such an energizing conversation! I’m really looking forward to seeing how Mytra continues to innovate and scale in the years ahead, while simultaneously pushing the boundaries of what automation could be.

CHRIS: Thank you, Tanya. It’s been a pleasure speaking with you.

The post Ecosystem Spotlight: Mytra appeared first on Silicon Foundry.

Tanya Privé had the pleasure of sitting down with Elaine to discuss how AI is reshaping corporate innovation, from governance and operating models inside global enterprises to the leadership, trust, and organizational alignment required to scale emerging technologies responsibly.

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TANYA PRIVÉ: Elaine, welcome! It’s great to have you with us. You’ve spent over two decades in the innovation space. As technologies like AI, advanced hardware, and automation have shifted from experimentation to core enterprise infrastructure, how has that changed the way you think about corporate innovation?

ELAINE: Tanya, thank you so much for having me! To start off, I’d say that transformation inside legacy brands is hard. I say that with a lot of respect for the people inside them. Throughout my career, I’ve seen a consistent push and pull. Leaders want to move quickly, while organizations are often structured to protect what already works.  Innovation teams are encouraged to experiment, yet kept at a distance from the core business. This tension often leaves innovation teams at arm’s length, well intentioned and interesting, but ultimately siloed and disconnected from how core decisions get made.

As AI and automation move from experimentation to core infrastructure, that separation is no longer sustainable. Innovation can’t live at the edges anymore; it must be woven into the very fabric of how the business runs. This realization shifted my perspective: innovation is not primarily a technology challenge—it is an alignment challenge. People, processes, and decision rights must move together. Without that alignment, even the most advanced technology struggles to create durable value.

TANYA: You touched on the tension between urgency and durability, which many leaders are wrestling with right now. Given the pressure companies feel to “do something” in AI, how should leaders distinguish between moves that build long-term positioning versus those that simply respond to short-term market noise?

ELAINE: The pressure to “do something” in AI is understandable, but it is often the wrong starting point. When leaders begin with urgency, they tend to optimize for visible action rather than durable advantage. Long-term positioning starts by slowing the question down. Instead of asking, “What tool should we deploy?” the more important questions are, “What problem are we truly solving?” and “What advantage are we trying to create?”

Short-term moves typically layer tools on top of existing processes to plug immediate gaps. While that creates activity, it rarely changes the trajectory of the business. Long-term moves reshape how the organization works, learns, and competes. I have seen repeatedly that redesigning how information flows across teams, rather than simply automating a single workflow, is what turns today’s solution into a compounding, sustainable advantage.

TANYA: How does the way large enterprises operate differ from scale-ups when it comes to modernizing the business, particularly around speed, scale, and brand risk?

ELAINE: Scale-ups operate in a phase where speed is existential. Product-market fit exists, but its durability, economics, and scalability are still being proven. Modernization is about removing friction fast enough to learn, adapt, and strengthen the business before competitors and market dynamics catch up.

Large enterprises operate from a very different starting point. They already have embedded relationships with millions of customers, where trust, loyalty, and brand reputation have been built over decades. This changes the equation entirely. For me, modernization is not just about what is technically possible; it is about what can be introduced without eroding customer confidence or breaking the promises they already rely on.

Inside global brands, every change carries a significant downstream impact, including regulatory exposure, brand risk, and employee readiness. This naturally introduces friction, and in many cases, I believe that friction is appropriate. The real risk occurs when that friction becomes silent resistance because teams are not aligned on the “why” or the trade-offs being made.

What I have learned is that speed inside enterprises is absolutely possible, but it looks different. It comes from clarity rather than pure urgency. It requires clear priorities, cross-functional alignment, and a leadership commitment to shared outcomes. Without that, teams often retreat into functional silos to protect their lanes. The most successful modernization efforts I have seen are anchored inside the business units, with technology acting as an enabler rather than the primary driver. That is how large organizations move forward without losing the trust that made them successful in the first place.

TANYA: You’ve also had a front-row seat to this inside one of the world’s most iconic brands. Specifically, during your time at Nike, what were the key lessons around governance, data readiness, and operating models when scaling AI across the organization?

ELAINE: The un-obvious lesson was that governance, when designed correctly, accelerates innovation rather than slowing it down. Early on, we made a deliberate choice to treat governance as an operating capability, not a checkpoint.

We built shared playbooks and clear risk thresholds to create what I think of as ‘governance by design.’ This provided teams an accelerated path to test and move into pilots without getting stuck in prolonged legal review cycles. On the data side, I saw that AI stalls where data ownership is fragmented. Therefore, I realized that treating data as a shared enterprise asset was foundational. Without that shift, no amount of tooling mattered. Speed at scale does not come from bypassing controls. Rather, it comes from designing them with intention, so innovation and trust advance together.

TANYA: What were the key takeaways from the session you led at Futureproof Project regarding how AI can shift the way brands communicate and engage with consumers, not just in efficiency, but also in creating meaningful experiences that drive trust?

ELAINE: The conversation consistently came back to trust and intent. What became clear is that AI is not changing brand engagement simply by making it faster or more efficient. It is changing how brands are experienced. I saw that increasingly, consumers do not encounter AI as a tool—they encounter it as behavior, tone, and presence. They respond emotionally to it.

One of the central ideas I shared is that AI allows brands to move from reacting to customers to anticipating them, not in a surveillance-driven way, but in a way that feels thoughtful and human. When a brand understands intent, context, and timing, interactions stop feeling transactional and start feeling supportive.

The most compelling examples were not about campaigns, but about continuous learning systems. Experiences that adapt over time, conversations that get smarter, and moments where automation actually creates more space for empathy rather than less. The brands that stand out are using AI to show up better, not louder. More consistent. More relevant. More human in moments that matter. When AI is used to deflect responsibility, consumers feel it immediately. When it is used to remove friction and add care, trust deepens.

From that conversation, the core takeaway was that efficiency is expected now, and trust is where differentiation begins. I also emphasized that AI does not ultimately replace the human relationship between a brand and its customers. It amplifies it, for better or worse.

TANYA: Over the next few years, where do you see the biggest opportunities for you and Silicon Foundry to shape how corporates engage with frontier technologies and innovation ecosystems?

ELAINE: I see a meaningful opportunity to help companies make better, earlier decisions as frontier technologies, especially AI, move faster than most organizational models can keep up. Silicon Foundry is in a rare position. It sits close to emerging technologies and venture ecosystems and is deeply grounded in the realities of running large enterprises. That vantage point allows us to do more than introduce innovation. It allows us to help leaders interpret signals, understand trade-offs, and make decisions that hold up over time.

From my experience inside large organizations, the hardest part is rarely discovering what is new. It is knowing what to do with it. How to align technology bets with business strategy. How to structure partnerships that actually scale. And how to design governance and operating models that allow teams to move quickly without eroding trust.

I am excited to work alongside Silicon Foundry to help companies engage with innovation ecosystems in a more intentional, repeatable way. One where technology, partnerships, and people are designed to work together as a system.

TANYA: Finally, looking ahead to the next five years, where do you think large enterprises are most likely to misjudge the complexity of AI and emerging technologies?

ELAINE: Many large enterprises will underestimate how fundamentally organizational this transformation is. While the technology itself will continue to improve at an extraordinary pace, those advances often mask where the real complexity lives: in people, incentives, and decision-making. The truth is, AI does not fail because of technical limitations; it fails when organizations try to layer it onto operating models designed for a different era.

The most common misjudgment is treating AI as a technical upgrade rather than a shift in how work actually gets done. In reality, it changes who makes decisions, how fast those decisions are made, and what skills matter most. This requires rethinking roles, incentives, and leadership behaviors, not just deploying new software. AI also has a way of exposing misalignment early. Where data is fragmented or priorities are unclear, AI amplifies those weaknesses. Conversely, where teams are aligned around shared outcomes, it compounds their strengths.

The organizations that succeed will be the ones that approach AI as a system-level change—aligning people, technology, and governance together. Success won’t come from chasing the latest tools, but from redesigning how the organization learns and adapts over time. 

TANYA: Elaine, thank you for such an informative conversation. I’m excited to see how your perspective influences the next wave of practical, human-centered AI adoption.

The post Meet Our Venture Partners: Elaine Barsoom appeared first on Silicon Foundry.

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Let’s start with the “why.” What inspired Silicon Foundry to create the Executive Treks offering?

Executives are increasingly curious about what’s happening on the frontlines of innovation, whether in Silicon Valley or other global hubs like London, Tel Aviv, or Singapore. However, they often lack the time, access, or structured format to deeply engage with startups, VCs, and trailblazing thinkers who are shaping the future.

Executive Treks were created to bridge that gap. They offer a highly curated, immersive experience that brings senior leaders face-to-face with the people and ideas that matter most. By stepping outside their traditional environments and engaging with cutting-edge technologies and business models, executives gain the insight, inspiration, and connections necessary to think differently and lead boldly.

Why do you believe the Executive Treks offering is particularly relevant right now?

The pace of technological change continues to accelerate, and business leaders are expected to make forward-looking decisions amid unprecedented complexity. Executives can’t afford to stay siloed. They need to experience emerging innovation ecosystems firsthand.

At the same time, the startup and venture ecosystem has matured. Solutions that were once considered too early are now robust, enterprise-ready, and capable of driving meaningful business transformation. But with this maturity comes an overwhelming volume of options. Executive Treks provide the filtering, curation, and translation layer that busy leaders need to identify the most relevant, high-impact solutions. They also serve as a forcing function for executives to step out of the day-to-day and see what’s possible, which is often the first step toward real innovation.

In your own words, how would you explain the impact this offering has on corporate leaders?

Executive Treks create a shift in mindset. By engaging in direct, in-person dialogue with entrepreneurs, investors, and pioneering corporates, executives are pushed to think beyond incremental improvements and toward transformational opportunities.

These experiences often catalyze new partnerships, inform strategic decisions, and unlock new ways of thinking about persistent challenges. They’re not just informational. They’re also inspirational and actionable. Whether it’s discovering a startup to partner with, learning from a peer’s innovation journey, or simply being jolted out of conventional thinking, the outcomes tend to have lasting impact.

What’s a misconception people often have about the Executive Treks?

A common misconception is that Executive Treks are a form of “innovation tourism,” a flashy, surface-level look at startups without meaningful outcomes. That’s not what we do. We design each trek with clear objectives in mind, aligning every meeting and experience to the client’s strategic priorities. The startups and thought leaders we include are not random or off-the-shelf. They’re carefully selected for relevance and potential fit.

Another misconception is that these treks are glorified sales pitches. In fact, we deliberately avoid that. We ensure executives are meeting with CEOs, founders, and senior leaders who can speak to long-term vision and strategic context, not just product specs.

Can you share a favorite anecdote or example where this offering really made a difference for a client?

We’ve seen several treks serve as a critical starting point in long-term strategic relationships. In many cases, the trek becomes the first step in a meaningful collaboration, whether it’s a pilot, partnership, or even investment.

For one client, meetings during their trek led to a strategic partnership with a startup in an adjacent industry, something they would not have considered previously. In another instance, years after a trek, a client executive cited a particular conversation with a startup founder as the seed that shaped a major strategic initiative.

These treks build trust on both sides. Corporates start to view emerging companies as serious innovation partners, and startups see a pathway to real engagement beyond a single meeting.

What’s something you personally learned or found surprising while building or delivering the Executive Treks offering?

The power of in-person engagement is real and hard to replicate. When executives sit across the table from founders or VCs, the energy and authenticity of the exchange lead to more memorable and actionable takeaways. I’ve also learned that when executives take time out of their schedules and immerse themselves in these experiences, they come in with a sense of “skin in the game.” That commitment leads to more open, high-level conversations and a greater willingness to move from idea to execution.

I’ve been struck by the level of alignment and mutual value that can be achieved when we design these treks thoughtfully. When both sides are prepared, the conversations go far deeper than surface-level networking. They become the start of real collaboration.

How do you see the Executive Treks offering evolving in the next 12-18 months?

We expect to see treks expand beyond traditional innovation hubs like Silicon Valley and New York to include emerging centers of innovation in Europe, the Middle East, and Asia. As global innovation becomes more decentralized, our clients are eager to explore diverse ecosystems and understand how innovation looks and operates across different markets. We also see an opportunity to involve a broader set of stakeholders, not just C-suite executives, but also heads of business units, product leaders, and transformation teams. This allows for multi-layered engagement and faster internal alignment post-trek.

We anticipate a greater emphasis on turning insights into action. More clients are asking us to help translate what they learned into next steps, roadmaps, or experiments, which is a natural extension of our advisory work.

If you could give one piece of advice to a corporate leader considering the Executive Treks offering, what would it be?

Think of Executive Treks not as an endpoint, but as a powerful starting point. They can spark ideas, reframe challenges, and expose you to entirely new possibilities, but the real value comes when you commit to taking action after the trek.

To create lasting impact, you need executive sponsorship, cross-functional alignment, and a willingness to experiment. When paired with Silicon Foundry’s broader suite of offerings, from discovery to execution, Executive Treks can serve as the launchpad for transformational innovation journeys.

What excites you most about working in this space?

What excites me most is seeing unexpected connections lead to breakthrough ideas. Often, the most valuable insights come not from your own industry, but from adjacent or even seemingly unrelated sectors. There’s immense creativity and potential at the intersections, such as retail technologies shaping the future of air travel or telecom infrastructure unlocking new financial services experiences, and beyond. Being in the room when those dots are connected and seeing the lightbulb go on for a corporate leader is incredibly rewarding.

We’re fortunate to work at the nexus of ambition and possibility, where forward-thinking leaders come to reimagine what’s next. That’s what keeps me inspired.

The post Inside Silicon Foundry: Managing Director Eli Promisel on Unlocking Innovation with Executive Treks appeared first on Silicon Foundry.

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TANYA PRIVÉ: We recently welcomed our Venture Partner, Alok K. Agrawal, to the team. Alok, welcome! We’re thrilled to have you on board!

ALOK K. AGRAWAL: Hi Tanya, thank you for having me!

TANYA: Let’s start with your experience as the Chief Strategy Officer at Celestica. You were a crucial part in leading its transformation as a major player in AI infrastructure and advanced hardware. What lessons can corporates draw from that experience about repositioning for the next decade of technology shifts?

ALOK: At Celestica, something crucial I learned was that repositioning isn’t a messaging exercise. You can see it in the budget and the organizational chart. The work is stepping back from areas where you can’t win long-term and putting real money into what customers will pay for, such as strong engineering, advanced manufacturing, and consistent execution. I’ve realized that small pilots won’t change a company on their own. Instead, what changes a company is leadership making hard calls while the legacy business is still profitable. If you wait until the old model stops, you don’t have many options left.

TANYA: That’s a fascinating insight, especially the idea that real transformation requires commitment while the legacy business is still strong. Many corporate M&A and venture efforts struggle to translate activity into sustained impact. From your work leading strategy, M&A, and Celestica Ventures, what separates high-impact corporate innovation models from the ones that stall?

ALOK: The difference is being clear about intent and being willing to act on what you learn. Strong programs know what each deal is meant to achieve: capability, speed, talent, customer access, or risk reduction, and they track whether that’s happening. Weaker programs hide behind “optionality” with no owner and no decision triggers, then count activity instead of outcomes. If the operating leaders don’t own the result, it stays on the side and never actually scales. And if you don’t shut down what isn’t working out and move resources, you end up with a portfolio that consumes attention without paying it back.

TANYA: Many of your investments focus on AI, space, defense, robotics, and automation – areas where corporates are trying to build capability quickly. Where do you see the most immediate opportunities for large organizations to partner or co-develop with startups?

ALOK: I would say the fastest opportunities are where you can put something into operations quickly and learn fast. You often find that in physical workflows—automation, inspection, logistics, maintenance, and field operations—where improvements show up in throughput, safety, reliability, or labor efficiency. Those environments let corporates and startups move beyond pilots and build something that runs day to day, not just in a lab.

However, on the AI side, a lot of near-term value is moving intelligence closer to where work happens. Power limits, latency, connectivity, and security often make “everything in the cloud” unrealistic. Edge approaches—perception, control, and decision-making integrated into existing systems—tend to pay back faster than broad platform bets. The common thread is partnering when speed and learning matter, and co-developing when the real-world environment is what makes the solution work.

TANYA: Shifting from how companies scale globally to how they access new capabilities, you’ve led both acquisitions and strategic partnerships. When leaders are evaluating emerging technologies, how should they think about the build-versus-buy-versus-partner decision?

ALOK: Build vs buy vs partner isn’t always the first decision. The better starting point is which companies matter to your strategy and what role they could play. Once that’s clear, the structure can evolve as you prove adoption and build conviction. Some of the best outcomes start with close collaboration to understand the technology and how it fits the business, then transforming it into a partnership, an investment, a commercial agreement, or an acquisition as the importance and confidence increase.

Where companies get stuck is picking a structure too early. For instance, they could treat partnerships as a low-effort option or push for an acquisition before they understand what integration will take. A practical pattern is to partner first to prove adoption, invest to deepen alignment, and acquire only when the capability is truly core and you’re prepared to integrate it.

TANYA: From your vantage point as a board member and investor, what are the early signals that a startup is ready — or not ready — for enterprise-scale collaboration?

ALOK: Some early signs that I look for are whether a startup is thinking beyond the initial sale. The ones that are ready often talk about integration, security, deployment, and reliability because they’ve already experienced and dealt with those realities. Furthermore, they have documentation, a plan for procurement and security review, and customer success or services that don’t depend on the founder stepping in every week. They understand that the hard part starts after the public offering, when the solution has to survive rollout and operate reliably at scale.

On the other hand, the not-ready pattern shows up quickly. They treat enterprises as bigger checks, underestimate compliance and data access, and don’t have a plan for what happens when the first deployment hits real-world friction. I’m often drawn to founders who came out of the industry because they’ve felt that friction firsthand. The demo usually isn’t the problem. Running in production is.

TANYA: Given your work building a venture syndicate and portfolio across critical infrastructure, what risks or blind spots should corporate leaders be paying closer attention to in 2025 to 2030?

ALOK: Leaders often underestimate how quickly assumptions change once plans meet reality. Supply and access can look stable until a single dependency—one supplier, one process step, one qualification—suddenly determines the entire roadmap. Moreover, geopolitical shifts can also force parallel tech stacks, duplicated compliance work, and separate operating models that drive cost and complexity much earlier.

Another blind spot is how messy “early progress” can become later. Rapid AI adoption can create scattered systems that are hard to govern and expensive to scale if the architecture isn’t thought through upfront. And the constraint that keeps showing up is people—not generic “AI talent,” but engineers and operators who know how to make complex systems run reliably in production. That capability takes time to build and becomes a limiting factor sooner than most teams plan for.

TANYA: Finally, looking ahead, where do you see the most compelling opportunities for you and Silicon Foundry to jointly support corporates in navigating frontier-tech ecosystems?

ALOK: Most corporates don’t struggle to find startups. The real challenge is turning early interest into something that actually runs at scale. The opportunity is helping teams move from pilot to production in a repeatable way, starting with a practical readiness check that separates a good demo from something that can operate reliably day to day.

That means being clear on partnership terms around IP and data, and having a real plan for what needs to change across IT, operations, and procurement to roll something out across sites. The goal isn’t just to get one project over the line, but to build muscle inside the company so it can do this again and again. That’s especially important in areas like AI infrastructure and industrial automation, where execution and reliability matter just as much as the underlying technology.

The post Meet Our Venture Partners: Alok K. Agrawal appeared first on Silicon Foundry.

Tanya Privé had to pleasure of sitting down with Ilya and diving into the early frustrations that sparked Craft’s creation, the evolution of its AI-first intelligent workspace, and the shifting definition of supply chain resilience in an era of constant disruption, displaying why visibility has become one of the most essential capabilities in modern procurement.

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TANYA PRIVÉ: Ilya, it’s a pleasure to have you here! Before Craft became the platform it is today, you were on the other side of the table, dealing with messy, unreliable data. What was the pain point that convinced you it was time to build a better solution?

ILYA LEVTOV: Tanya, thanks for having me! When I founded Craft, I was coming out of a 15-year career in business development and finance roles in Silicon Valley and various technology companies. During that entire time, I found myself hunting for company information almost every day, whether I was buying from a company, selling to them, investing in them, or evaluating a potential partnership. 

To me, the experience was almost always frustrating. The data was always missing, outdated, inaccurate, or simply unavailable. So, I began to wonder: Could there be a better way?

Could we build for companies what Zillow and Trulia built for homes, or what Yelp built for restaurants—a reliable source of truth?

That idea became the foundation of Craft. We started by building crawlers and scrapers to gather data directly from company websites—homepages, “About” pages, job listings, management team profiles, pricing pages, and more. Then, we cleaned it up and built real company profiles. The demand was almost immediate, and soon, we were appearing in more than 100 million organic search results per month, all without paid marketing.

Over time, we saw that procurement and supply chain teams across both large enterprises and government agencies were using Craft to understand and monitor hundreds of thousands of suppliers at once. That discovery reshaped our focus entirely, and we’ve been dedicated to serving supply chain and procurement leaders ever since.

TANYA: Craft’s platform ingests internal and external data to surface supplier risk insights. In simple terms, how does your data intelligence engine work end-to-end, and how do you keep insights timely and accurate?

Ilya: Craft has evolved tremendously from those early days of basic scrapers. One of the biggest steps forward was forming partnerships with best-in-class specialty data providers covering cybersecurity, ESG, financials, media, reputation, and other key categories. In many cases, we work with multiple high-quality partners for the same category to ensure accuracy and coverage.

We blend those external sources with extensive native data collection, which over the last few years has become agentic. Today, AI agents continuously gather and interpret publicly available data, which we merge with our partner datasets to create a highly validated, multi-sourced data fabric.

We also rely on an exceptional human-in-the-loop team to verify and refine data. That combination of AI scale, specialty partnerships, and human validation ensures Craft’s insights are both comprehensive and trustworthy.

TANYA: As Craft has evolved from a data source into a full workspace for procurement and supply chain teams, you’ve also raised significant capital along the way. With $42 million raised across your Series A and B, what strategic priorities are you focused on—technology, market expansion, talent, or partnerships?

Ilya: We’re now fully in the era of AI, and our top investment priority is the evolution of our intelligent workspace—our AI-first product. It is what takes Craft from a powerful database into an immersive, end-to-end workspace for procurement and supply chain teams. This product fundamentally changes how enterprises qualify suppliers, assess risk, and perform continuous monitoring across their entire supplier network. AI is the key to unlocking that transformation.

Beyond product innovation, we’re investing heavily in sales and marketing in order to broaden awareness of Craft, engage prospective customers, and equip our team with the tools needed to bring those customers on board.

TANYA: Craft became a crucial resource during the COVID-19 supply chain crisis. What were the biggest lessons from that period, and how did it shape your long-term vision?

Ilya: The pandemic exposed how brittle global supply chains truly were. Years of “just-in-time” manufacturing, offshoring, and heavy dependence on China and Asia created extreme fragility. In those early months, supply chains all but collapsed, and the world felt the consequences, down to basic necessities disappearing from store shelves.

Even after the initial crisis passed, organizations realized that deeper structural issues still remained, such as an overreliance on overseas suppliers, fragile shipping routes, and volatile shipping and oil prices, ESG concerns like forced labor and environmental violations, and ever-persistent cybersecurity risks within supply chains

COVID-19 was the catalyst, but the wake-up call continued long after. The positive outcome is that enterprises and government agencies have remained focused on building and maintaining supply chain resilience, and Craft is now deeply aligned with that mission.

TANYA: You noted earlier how teams were spending entire days compiling supplier risk reports before Craft. Where have you seen Craft drive the most measurable impact—time saved, risk reduced, or operational efficiency?

Ilya: I would say the most immediate impact is time savings. Many customers previously spent 8 hours manually researching and preparing a supplier risk report. However, we brought that down to 1 hour, and with the intelligent workspace, it now takes about a minute to generate a comprehensive, validated assessment. 

The second major impact is risk reduction. Across large supplier networks, Craft typically uncovers previously unknown material risks in 15–24% of suppliers in any given product line. That early detection allows supply chain leaders to mitigate issues long before they become disruptions.

TANYA: Supply chain and procurement teams face immense pressure today. How has the definition of supply chain resilience evolved since you founded Craft, and where is it heading next?

Ilya: Definitely one of the most important shifts is from point-in-time monitoring to continuous monitoring. 80% of supply chain risks emerge after onboarding, which highlights the need for ongoing visibility rather than annual check-ins.

But frequency is only part of the transformation. The scope of risk assessment has expanded dramatically. Traditional checks focused almost exclusively on financial health. Today, organizations must evaluate cybersecurity posture, environmental and social responsibility, geopolitical exposure, climate and location risks, and shipping route vulnerabilities.

In many cases, these alternative signals outperform traditional credit ratings in predicting future instability. The future of resilience is truly 360-degree, continuous, multi-signal monitoring.

TANYA: Outside of continuous monitoring, what is Craft’s core differentiator versus legacy tools or newer market entrants?

Ilya: Our greatest differentiator is our data fabric—the breadth, depth, and validated quality of our data. It combines high-scale AI, multi-sourced datasets, and human verification in a way that no other player matches. On top of that foundation sits our AI-first intelligent workspace, introduced in late 2024 and expanded throughout 2025. It enables enterprises to qualify suppliers 80% faster than before and to continuously and comprehensively monitor their supply chains.

Together, these capabilities deliver tremendously powerful and actionable insights that transform how organizations manage suppliers and risk.

TANYA: Hearing the full arc of Craft’s journey, from a simple idea about reliable company data to a platform supporting federal agencies, what has been one of the most defining moments for you so far? And as you look ahead, what should we expect next?

Ilya: The entrepreneurial journey has been so exciting and at the same time, deeply unpredictable. I think it’s extremely rewarding that there’s a new problem to solve every day. Craft’s path from a general source of truth on companies to a leading supplier intelligence platform has been nonlinear, but incredibly worthwhile.

Building this team of exceptional, diverse, passionate individuals has been one of the greatest privileges of my career. And seeing the real impact we have on customers, especially across the U.S. federal government, is profoundly meaningful.

Looking ahead, our focus is on continuing to elevate the intelligent workspace and expanding the impact we deliver to global supply chains. We’re just getting started.

The post Ecosystem Spotlight: Craft’s Vision for Smarter Procurement appeared first on Silicon Foundry.