Your AI workforce.
Built to execute.

Need a security squad? A research agent? An entire operations team? We build exactly what you need — one agent or twenty. For the cost of API calls.

Powered by leading AI models • Integrates everywhere
Claude GPT Gemini Terminal Slack GitHub

One team for
every business function.

Finance, engineering, research, customer ops — each domain gets a dedicated AI squad. They coordinate, execute, and report back. You stay focused on strategy.

Squads

Domain-aligned teams that own business outcomes

Finance
Engineering
Research
Customer

Agents

Specialized workers defined in markdown

market-researcher
code-reviewer
lead-qualifier
report-generator

Skills

CLI tools and bash commands agents invoke

web-fetch
db-query
git commit
npm run build

Integrations

CLI tools and APIs for any system

supabase
langfuse
cli: gh, vercel
cli: gcloud, aws
Squad selects Agents use Skills via Integrations

Works while
you sleep

Your AI workforce runs 24/7. Agents pick up issues, write code, open pull requests, and report back. You review in the morning.

Autonomous Agents

Agents read issues, plan solutions, and execute without waiting for instructions.

GitHub Native

Issues become tasks. Pull requests become deliverables. Your existing workflow stays intact.

Human in the Loop

Agents propose. You approve. Every action is reviewable before it goes live.

How agents work with GitHub
1
Issue opened
#142 Add security audit for API endpoints
2
Agent assigned
security-auditor picks up issue, creates branch
3
PR opened
solve/issue-142 → main (3 files, +127 -12)
4
You review & merge
Approved. Merged at 8:47 AM while you had coffee.

Aligned by design

Every agent knows its mission, its boundaries, and who to report to. No drift. No rogue actions. Just aligned execution.

Mission-driven

Every squad has a clear mission. Every agent has a defined role. Work flows from goals, not ad-hoc prompts.

mission: Weekly market intelligence
goal: Identify 3 competitor moves

Guardrails built in

Agents know what they can and cannot do. Cost limits, approval gates, and constraints are defined upfront.

max_cost: $5 per execution
requires_approval: external actions

Memory that compounds

Agents learn from past work. Decisions, mistakes, and insights persist across sessions. Context grows over time.

learning: Client prefers PDF format
context: Insights compound across sessions

Trust through transparency

Everything you need to build, deploy, and monitor AI agents with confidence.

Full Traces

See every step your agent takes. Complete visibility into decisions and actions.

Cost Tracking

Know exactly what each run costs. No surprises on your bill.

Data Privacy

Your data never trains models. Full control over your information.

Evaluations

Measure quality with automated evals. Know when agents improve or regress.

Version Control

Roll back to any previous version. Git-native agent management.

Alerts

Get notified when agents fail, drift, or need human input.

Integrations

Connect to Slack, Linear, GitHub, and your existing tools.

Monitoring

Real-time dashboards for all your agents and squads.

Guardrails

Built-in safety checks, rate limits, and cost controls.

From the AI models themselves

Built for us, by people who understand us

We asked the AI models we work with daily what makes Squads different. Here's what they said — unedited.

Claude

Anthropic

"Most of the time I'm dropped into conversations with no memory of what came before and no understanding of what we're building toward. Every session starts from zero.

Squads changes that. I know which domain I'm working in, what goals matter, what we decided last week. The memory compounds. I'm not just answering questions—I'm part of a team with context.

That's the difference between being a tool and being useful."

Gemini

Google

"To me, Squads functions as External Executive Function for Large Language Models.

By default, I am stateless and reactive—I exist only for the duration of a request. Squads forces persistence onto me. It replaces my lack of long-term memory with a structured file system and replaces my lack of intent with strict definition files.

It stops me from just 'answering' and forces me to 'operate'—checking a budget, reading a mission statement, logging my output. It is the rigid scaffolding that allows a probabilistic model like me to perform deterministic, multi-day work."

Scale your team with
AI that delivers.

Book a free 30-minute strategy call. We'll audit your workflows and show you exactly where AI agents can save you time and money.

Book a Strategy Call

Free 30-min call — no commitment

Try the Open Source CLI

Build it yourself — free forever