Utilities today are navigating increasing climate impacts, heightened regulatory expectations, and growing pressure to improve reliability and safety. One of the most critical areas of focus is vegetation management.

At DTECH, Sharper Shape will host a live session featuring Brian House (Pacific Gas and Electric Company) and Chris Beaufait (Sharper Shape) that examines how technology is reshaping the way utilities manage vegetation risk.

The discussion will focus on how combining high-resolution aerial imagery, LiDAR, machine learning, and advanced analytics can provide a more complete, prioritized understanding of vegetation threats across the grid. Rather than relying on fixed cycles and reactive responses, utilities can shift toward predictive, risk-informed planning.

Participants can expect practical takeaways, including:

• How to design a more predictive approach to vegetation and infrastructure management
• Ways to prioritize work based on actual risk rather than routine schedules
• How advanced analytics can integrate into existing utility workflows
• What measurable operational benefits utilities are seeing from these strategies

PG&E will also offer firsthand perspective on deploying data-driven vegetation management at scale, sharing real-world experience, challenges, and results.

This session is well-suited for utility leaders, operations teams, and vegetation management professionals seeking to strengthen grid resilience while making smarter use of resources.

About Sharper Shape

Sharper Shape builds Living Digital Twin (LDT) software to help power transmission & distribution utilities and other operators of linear infrastructure manage risk, improve safety, and create operational efficiencies. Delivered on a cloud based, SaaS platform and supplemented by data collection and work package execution services, Sharper Shape’s technology is built by some of the brightest tech minds in Finland and the US. Our ever-expanding library of advanced AI/ML algorithms allows us to produce LDTs which are easy to integrate into user workflows and to update with live field data. Our ultimate vision is a safer world, and our mission is to create these tools and offer insights which empower asset operators to make it so.

Sharper Shape was founded in 2013 in Helsinki, Finland. Sharper Shape serves tier one utilities around the world, with dedicated technology centers in Helsinki and Salt Lake City, Utah.

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That is where two powerful technologies come into play: data lakes and digital, or data, twins. While they serve different purposes, when used together, they provide a foundation for smarter, faster, and more proactive grid management.

What is a Data Lake and Why Should Utilities Care?

Before diving into why data lakes become even more powerful when paired with a digital twin, it is important to first understand what a data lake is. At its core, a data lake is a centralized system that stores raw data exactly as it is. Whether the information is structured, unstructured, or somewhere in between, it is preserved in its native form. For utilities, this could include drone footage, LiDAR scans, maintenance logs, weather data, sensor readings, and GIS maps. Unlike traditional systems that require data to be cleaned and sorted before storage, a data lake allows utilities to keep everything intact and organize or interpret it later depending on the project.

This capability matters because utilities generate enormous amounts of data across departments that rarely communicate with one another. In many organizations, vegetation management teams cannot easily access inspection reports generated by aerial crews, and sensor data might be trapped in specialized formats that other departments cannot interpret. A data lake eliminates these barriers, creating a shared hub where information is stored and made available for anyone who needs it.

Even more importantly, data lakes use what is known as a schema-on-read approach. This means that users do not need to decide upfront how the data will be used. Instead, they can apply different organizational methods later depending on the question they are trying to answer. For utilities that generate terabytes of information each year, this flexibility is essential. The same dataset might be valuable to an operations team investigating storm damage, to a planning team modeling load growth, or to a vegetation management team analyzing tree encroachment patterns.

By breaking down silos and making data more accessible, a data lake creates better coordination, smarter analysis, and stronger decision-making across the entire organization.

What is a Digital Twin?

If a data lake is the library where information is stored, a digital twin is the living model that brings that data to life. A digital twin, sometimes referred to as a data twin, is a virtual replica of a real-world asset or system. This could be a substation, a single transmission line, or an entire segment of the grid. What makes a digital twin powerful is not just its ability to represent physical assets visually, but its ability to incorporate live data feeds that reflect real-world conditions in real time.

Through this connection, utilities can monitor operations, simulate disaster scenarios, and predict outcomes using both real-time performance metrics and historical patterns. A utility might, for instance, simulate how an incoming windstorm could affect a transmission corridor based on current load, the condition of nearby assets, and weather forecasts. This type of foresight enables utilities to act proactively, rather than reactively, and positions them to reduce risk and improve reliability.

Another advantage of digital twins is their ability to learn. The more inputs they receive, whether from aerial inspections, IoT sensors, LiDAR scans, or satellite imagery, the more accurate and intelligent they become. Over time, this creates a system that is not only descriptive but also predictive. Digital twins can highlight threats before they escalate into outages, identify areas of concern with surgical precision, and help utilities take preventive action. It is this blend of visualization, analytics, and foresight that makes digital twins one of the most disruptive technologies in utility operations today.

Why They Are Better Together

While data lakes and digital twins can each stand on their own, their true potential is realized when they are combined. Data lakes are excellent at handling the past, storing years of historical information that would otherwise remain unused. Digital twins excel at handling the present, providing real-time awareness and predictive capabilities. When these two are linked, utilities gain the ability to handle the future.

The data lake provides the deep historical context that a digital twin needs to make its predictions more accurate. A digital twin simulating vegetation risk, for instance, can perform far better when it has access to years of tree growth patterns, outage history, and inspection records stored in the data lake. This combination creates insights that are not only predictive but also highly actionable. Utilities gain systems that are smarter, more precise, and more reliable than what either technology could achieve alone.

Together, data lakes and digital twins form an engine for continuous improvement. The digital twin consumes live and historical data, produces new insights, and those insights can then be fed back into the data lake for future analysis. This feedback loop compounds value over time and drives better outcomes across operations.

What an Ideal System Looks Like for a Utility

Utilities that embrace both data lakes and digital twins build a grid that is more agile, resilient, and intelligent. The benefits ripple across nearly every function of the organization.

During storm response, for example, outage records stored in the data lake can feed into digital twins to model storm paths and identify the most vulnerable assets. With this information, utilities can deploy crews in advance to the right locations, reducing downtime and minimizing damage. In vegetation management, years of growth and encroachment data stored in the data lake can be combined with real-time aerial imagery in the digital twin to prioritize trimming in areas that pose the highest risk.

The integration also streamlines the adoption of renewable energy and distributed energy resources. By using digital twins to simulate how new solar arrays, wind farms, or battery systems will interact with the grid before deployment, utilities reduce risk and accelerate planning. This capability becomes especially valuable as utilities work to maintain stability while bringing more renewable resources online.

Inspection planning is another area transformed by this integration. Instead of scheduling broad sweeps across an entire service territory, a digital twin can highlight precise areas that show early signs of degradation or risk. Crews can then be directed to focus only on assets that need attention, saving time, reducing labor costs, and ensuring more efficient use of resources.

The larger implication is that integrating data lakes and digital twins moves utilities from a reactive mode of operation to a predictive and proactive one. Instead of waiting for outages to occur, utilities can anticipate them and act beforehand. Instead of investing broadly in costly upgrades, they can target spending where it delivers the greatest impact. Instead of struggling to keep up with an evolving grid, they can take control of it.

Preparing for the Future

The pressures facing utilities today will only intensify. Aging infrastructure, growing energy demand, climate-driven risks, and the push toward decarbonization require new tools and approaches. Data lakes and digital twins are not just technologies that solve today’s problems. They are foundational capabilities for the future of the grid.

Utilities that embrace this pairing will find themselves better equipped to manage risk, optimize investments, and deliver reliable service to their customers. Those that do not may find themselves constrained by data silos, outdated processes, and limited visibility into their systems.

In the end, the message is simple. Data is only as valuable as the insights it produces. A data lake ensures utilities can collect and preserve everything. A digital twin ensures they can make sense of it and put it to work in real time. Together, they provide the intelligence needed to build a grid that is smarter, stronger, and ready for whatever challenges lie ahead.

By Kristy McDermott, Vice President of Sales at Sharper Shape

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What Is LiDAR—and Why Is Classification Critical?

LiDAR (Light Detection and Ranging) captures billions of 3D data points that map every detail of utility infrastructure and surrounding environments. From power lines to substations to nearby vegetation, LiDAR delivers unmatched visibility. But those raw points alone don’t tell a story—they need classification.

Classification transforms raw data into actionable insights by labeling each point (e.g., tree, conductor, pole, ground). This enables electric utilities to:

• Spot and address vegetation risks before they trigger outages or fires
• Monitor pole lean, wire sag, and asset health
• Ensure regulatory compliance with precise clearance data
• Plan for storm response, grid upgrades, and emergency management

Without accurate classification, LiDAR is just noise. With it, utilities gain clarity and control.

The Manual Bottleneck—and Why It No Longer Works

Traditional LiDAR workflows rely on manual annotation and rule-based algorithms—time-consuming processes that can’t keep up with today’s scale. Modern utility scans can span hundreds of square miles and billions of points, requiring months of processing time and often risky overseas outsourcing.

These methods are reaching their limit in terms of speed, cost, and scalability.

AI LiDAR Classification: The Utility Game-Changer

AI, especially deep learning, is reshaping how LiDAR data is processed. Instead of relying on static rules, AI models learn from labeled datasets to automatically identify even subtle or overlapping features—like power lines obscured by trees.

With AI, utilities can:

• Classify large datasets in hours instead of weeks
• Handle complex, cluttered environments with higher accuracy
• Automate QA/QC to flag anomalies and ensure data reliability
• Minimize manual input while increasing precision

The result? Actionable, high-confidence insights delivered in days—not months.

What to Look for in a Classification Tool

Choosing the right tool is about more than speed. Utilities should prioritize:

• AI-first workflows for maximum efficiency
• Advanced feature extraction (e.g., buildings, conductors, ground segmentation)
• Scalable architecture for handling billions of points
• Interactive 3D visualization for intuitive data interpretation
• Hybrid workflows that combine automation with expert review where needed

The best tools don’t just classify data—they transform it into decision-ready intelligence.

What’s Next: AI + LiDAR + Real-Time Utility Ops

The future is even smarter. Upcoming advances in predictive modeling will allow utilities to forecast vegetation growth, detect asset fatigue, and assess fire risk—before problems occur. Edge computing will enable real-time LiDAR classification onboard drones or vehicles. And system integrations will feed classified data directly into GIS and maintenance platforms, streamlining response and planning.

As sensor costs drop and AI matures, this technology becomes accessible to utilities of all sizes—ushering in a new era of smarter, more resilient grid management.

Conclusion: Ready for the Power Play?

AI-powered LiDAR classification isn’t just a technical upgrade—it’s a strategic leap forward. For utilities facing rising demands and limited resources, it enables faster, smarter, and safer infrastructure decisions.

At Sharper Shape, we help utilities turn point clouds into power plays—with AI-driven classification that delivers accuracy, scale, and impact. Because the grid of the future doesn’t wait—and neither should your data.

The post From Point Clouds to Power Plays: How AI LiDAR Is Supercharging Utility Grids appeared first on Sharper Shape Inc..

LiDAR Insights is designed to classify LiDAR point clouds with unmatched reliability and precision automatically. Leveraging a state-of-the-art AI engine, the system supports 29 electric utility network-specific classes—streamlining workflows and dramatically reducing the time and cost associated with traditional LiDAR data processing.

“With our new AI-powered LiDAR Insights, we’re taking the guesswork and labor out of classification,” said Chris Beaufait, President & CEO at Sharper Shape. “This means our customers can now receive mature, actionable LiDAR deliverables in a fraction of the time, and at a significantly lower cost.”

“We built the LiDAR Insights with geospatial professionals in mind—knowing their need for speed, accuracy, and seamless integration,” said James Conlin, Director of Product and Customer Success at Sharper Shape. “By automating classification with utility-specific intelligence, we’re helping utilities unlock the true potential of their LiDAR data—quicker, cheaper, and smarter than ever before.”

Seamlessly integrating into existing workflows, LiDAR Insights doesn’t just optimize classification—it elevates it. Whether used for vegetation management, asset inspection, or grid modernization, this new offering enables utility operators and geospatial professionals to achieve faster turnarounds and superior results.

LiDAR deliverables of all types just leveled up!

About Sharper Shape

Sharper Shape builds Living Digital Twin (LDT) software to help power transmission & distribution utilities and other operators of linear infrastructure manage risk, improve safety, and create operational efficiencies. Delivered on a cloud based, SaaS platform and supplemented by data collection and work package execution services, Sharper Shape’s technology is built by some of the brightest tech minds. Our ever-expanding library of advanced AI/ML algorithms allows us to produce LDTs which are easy to integrate into user workflows and to update with live field data. Our ultimate vision is a safer world, and our mission is to create these tools and offer insights which empower asset operators to make it so. 

Sharper Shape was founded in 2013 and serves tier one utilities around the world, with dedicated technology centers in Helsinki, Finland and Salt Lake City, Utah.

For more information, visit www.sharpershape.com.

The post Sharper Shape Launches LiDAR Insights: Revolutionizing LiDAR Classification with AI-Powered Efficiency appeared first on Sharper Shape Inc..

We explore four major asset management challenges faced by T&D utilities, along with practical solutions for each.

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The AI Breakthrough Awards program is renowned for evaluating the most promising AI companies from around the world, with more than 5,000 nominations submitted this year alone. Winners are selected by a panel of industry experts based on innovation, performance, ease of use, functionality, and impact. Past winners include global leaders such as IBM, NVIDIA, and Intel—underscoring the prestige and competitive nature of this recognition.

Sharper Shape’s award-winning solution is powered by CORE (Cloud Optimized Remote Evaluation), its AI-driven platform that processes LiDAR, imagery, and other data to build a dynamic, visual representation—or Living Digital Twin—of utility infrastructure. This visualization enables utilities to understand, inspect, and manage their assets with a level of precision and proactivity never before possible.

“Our team is honored to be recognized by the AI Breakthrough Awards for our work in utility data visualization,” said Chris Beaufait, CEO at Sharper Shape. “This award validates our mission to revolutionize utility operations by making massive volumes of complex data understandable and actionable. We’re proud to empower utilities to make smarter decisions that protect people, infrastructure, and the environment.”

Sharper Shape’s CORE platform is already being used by major utilities to reduce truck rolls, inspect assets, ensure regulatory compliance, and wildfire risk mitigation. The platform’s visual insights help transform traditional grid management into a proactive, data-first discipline.

About Sharper Shape
Sharper Shape builds Living Digital Twin (LDT) software to help power transmission & distribution utilities and other operators of linear infrastructure manage risk, improve safety, and create operational efficiencies. Delivered on a cloud-based, SaaS platform and supplemented by data collection and work package execution services, Sharper Shape’s technology is built by some of the brightest tech minds in Finland and the US. Our ever-expanding library of advanced AI/ML algorithms allows us to produce LDTs that are easy to integrate into user workflows and to update with live field data. Our ultimate vision is a safer world, and our mission is to create tools and insights that empower asset operators to make it so.

Sharper Shape was founded in 2013 in Helsinki, Finland. It serves tier-one utilities worldwide and has dedicated technology centers in Helsinki and Salt Lake City, Utah.

For more information about Sharper Shape and its award-winning technology, visit www.sharpershape.com.

The post AI Breakthrough Honors Sharper Shape’s Living Digital Twin with Top Data Visualization Award appeared first on Sharper Shape Inc..

What’s next?

For DSPs in the T&D utility sector, asset management software should be an essential part of your toolkit for today and for tomorrow. By embracing these sophisticated systems, providers can ensure their services are not only competitive but also aligned with the digital transformation of the industry. As utilities themselves continue to face growing demands and challenges, the integration of advanced asset management solutions like Sharper CORE will be key to maintaining reliability and efficiency in their operations, and they’ll demand the same of their partners.

Get in touch with us to learn more!

The post The benefits of asset management software for drones in T&D utilities appeared first on Sharper Shape Inc..

Utilities face significant challenges with aging infrastructure, extreme weather, rising operational costs and increased demands for reliability. AI offers a promising solution, but it’s time to move beyond theoretical discussions, the ‘what ifs?’, to embrace the practical benefits, the ‘what now?’.

AI tools like ChatGPT have already laid foundations as household names, receiving both good and bad reviews for varying applications and being put to use for everyday tasks. But the world is also abuzz with what feels like everyone pushing their latest and greatest AI solution that promises the world. With this can bring AI-fatigue. Without real, meaningful use cases of the benefits artificial intelligence can bring, we risk talking the talk, but not walking the walk.

Recent advancements show how AI can revolutionize asset management for utilities. Automated systems can now accurately identify and assess components on utility poles, streamlining inspections and minimizing human error. These systems not only detect defects with high precision but also enhance maintenance efficiency, reduce downtime, and extend the lifespan of critical assets.

This shift from talk to action signals the next step towards the future of utility management. After all, actions speak louder than words.

AI in action

To turn the theoretical into the practical, we can examine how AI technologies are already impacting the utility sector through innovative applications. For utilities especially, AI technology is no longer merely an experimental tool, but a proven solution. At Sharper Shape, we’ve been embedded in automating asset management for utilities for over a decade, honing what AI can look like and what it can provide for businesses with hundreds of miles of powerlines in the most remote locations. And of course, the industry has come a long way in the past ten years. Comparably, think of the smart phone you carried with you in 2014 versus Apple’s latest iPhone 16.

The most advanced software goes far beyond the machine learning that your summer intern could train in a couple of hours. And that’s not to undermine the work of interns, but today we’re deploying highly sophisticated tools that organize huge quantities of reality data into useable workflows. In recent years, many utilities have already made the first step to limit reliance on outdated physical maps, and instead found themselves relying on a digital equivalent – vast volumes of unorganized, siloed data which is unmanageable and expensive to store.

The next stage is truly AI-optimized systems which work through the entire inspection process from planning through to reporting, combining and interconnecting data as it does so, providing a clear and actionable plan giving utilities move oversight than ever before.  

One such platform is our Asset Insights module. By automating the detection and assessment of infrastructure components, employing advanced machine learning algorithms to scan utility poles and other assets AI solutions provide exceptional accuracy. This technology not only identifies defects such as cracks or corrosion but also assesses overall asset health, allowing utilities to prioritize maintenance and repair tasks effectively.

The real-world application of such technologies is already showing promising results. For example, utilities using AI-driven systems report a substantial reduction in both the time and cost associated with routine inspections. By automating these processes, AI helps utilities redirect valuable human resources towards more complex issues that require human insight.

Addressing the challenges

While AI offers substantial improvements, adopting it in utility asset management is not without its challenges. Integrating advanced AI systems into existing operational frameworks often presents hurdles in the form of employee training and data compatibility and system integration.

Utilities, and AI service providers, must address these technical challenges head-on, ensuring that their existing processes can seamlessly connect with AI technologies to fully leverage their capabilities.

Merging AI technology with legacy systems poses a significant challenge. Many utility companies operate on outdated platforms that are not readily compatible with the latest AI software, requiring extensive customization and sometimes complete system overhauls. This integration process demands not only technical expertise but also a strategic approach to ensure that new and old systems communicate effectively without disrupting ongoing operations.

Additionally, for AI to be effective, it requires high-quality, structured data. Utilities often have vast stores of unstructured or inconsistent data, making it difficult to leverage AI effectively. Establishing robust data governance and quality control is essential to prepare for AI integration. The process of cleaning and organizing data can be resource-intensive but is critical for maximizing the benefits of AI.

Training and change management also play crucial roles in the successful implementation of AI. Utility workers must be trained not only on how to use new systems but also on how to interpret AI-generated insights effectively. In an industry with an experienced workforce, the cultural shift towards data-driven decision making can be substantial and requires careful management to align staff with new technological processes.

Furthermore, the upfront cost of implementing AI can be a barrier, particularly for smaller utilities or regional cooperatives. However, the long-term cost savings, increased efficiency, and improved asset management performance justify the investment. To mitigate these costs, some utilities opt for phased implementation strategies, starting with the most critical assets to generate quick wins and establish the value of further investment.

Overcoming these challenges requires a proactive coordinated effort between AI solution providers and utility companies, focusing on seamless integration, comprehensive training, and strategic investment to ensure that AI tools deliver on their promise to transform utility asset management, while remaining flexible and scalable to best suit the utility’s needs. Such strategic integrations will enable early adopters to enhance their operational efficiencies without overhauling their entire systems.

Looking ahead

Looking ahead, the role of AI in utility management is set to grow exponentially.  Emerging trends such as the Internet of Things and smarter grids are expected to further enhance the capabilities of AI systems. These technologies will allow utilities to not only monitor but also automatically adjust their operations in real-time to optimize energy distribution and respond to potential disruptions before they escalate.

Moreover, as utilities continue to face the challenge of extreme weather AI will allow them to stay one step ahead of the status of surrounding vegetation that could fall onto powerlines or catch fire. Advanced data analytics powered by AI will provide enhanced decision-making, as AI algorithms analyze vast amounts of data to predict potential failures before they occur.

From discussion to action

In 2024, AI is already transforming utility asset management from a reactive to a proactive discipline. By harnessing the power of AI, utilities are not only improving their operational efficiencies but are also setting the stage for a future where digital resilience defines utility industry leaders.

The journey from theoretical AI applications to practical, impactful implementations is complex but achievable with strategic planning, robust partnerships, and a clear focus on long-term goals.

As we move beyond the hype, it becomes clear that AI is not just a tool for innovation but a necessity for the sustainable, efficient, and resilient utility operations of today and tomorrow.

By Kristy McDermott, Vice President of Sales at Sharper Shape

The post Turning Data into Decisions: AI’s Role in Next-Gen Utility Asset Management appeared first on Sharper Shape Inc..

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AI is revolutionizing industries across the world by enhancing operations and innovation. From diagnosing diseases in healthcare to optimizing manufacturing processes, AI’s influence is evident and it’s growing. Its integration into various sectors not only boosts efficiency but also tackles significant challenges, setting new standards in business practices and infrastructure management.

AI-driven data analysis

AI transforms UAVs into advanced diagnostic tools capable of real-time data processing. These intelligent systems analyze aerial imagery and sensor data to detect infrastructural anomalies such as wear and tear on lines or vegetation encroachment. This capability not only enhances the accuracy of inspections but also reduces the time taken to relay crucial information back to decision-makers, thereby facilitating quicker responses to potential issues.

Learn more about AI for DSPs

Optimizing flight operations

AI also plays a pivotal role in optimizing UAV flight operations. Through sophisticated algorithms, AI enables dynamic adjustment of flight paths based on real-time environmental data, such as weather changes or unexpected physical obstacles. This adaptive planning ensures comprehensive area coverage and maximizes data collection efficiency. Additionally, AI’s predictive capabilities allow for better scheduling of inspections, minimizing disruptions caused by adverse weather and ensuring consistent power supply for those who depend on it.

Make time and money savings with Sharper CORE

Enhancing UAV maintenance and safety

Beyond operational logistics, AI significantly boosts UAV maintenance protocols and safety measures. By implementing predictive maintenance, AI algorithms can analyze data from UAV sensors to forecast potential system failures before they occur. This proactive approach not only extends the lifespan of the UAVs but also ensures they operate within safe parameters. Furthermore, AI-enhanced navigational systems help maintain UAV stability and adherence to stringent aviation regulations, reducing the risk of accidents.

Find out more about how other DSPs are using Sharper CORE

Double down on digital

The integration of AI into UAV operations within the T&D sector marks a leap towards more automated, reliable, and efficient infrastructure management. By leveraging AI, companies can achieve higher operational standards, improved safety, and better data-driven decision-making. As this technology continues to evolve, its adoption will undoubtedly become more widespread, setting new benchmarks for the industry.

To speak to a member of our team about our solutions, please click here.

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