For in-house digital product teams

Most teams use AI.
Few are agent‑driven.

Expert agents, trained to your codebase and your domain. Each owns a role on your team, from the first spec to the final deploy.

EU-sovereign & AI-Act readyYou stay in controlStarts with one agent

Built by people who spent 20 years delivering enterprise software.

What we bring

A platform to run expert agents, and a team to make them work.

Expert agents, each great at one thing, onboarded to your stack and how your team works. They clear your backlog and catch what breaks, so your team can build what's next.

The platform
Aitonomy Control

Expert agents with real roles, deployed across your stack and governed by you.

The team
Aitonomy FDE

Embedded in your team to onboard your agents and own the delivery.

Aitonomy ControlEU region
Your team
6 agents · 5 live
Works with your stackGitHubGitLabJiraAzure DevOpsSlackMore +any model, any IDE
Who it's for

For in-house development teams.

Your product, your roadmap, more ambition than hands. Built for teams ready to move, and leaders with bigger plans than the headcount.

CTO

You own the AI strategy

…but right now
  • Spend up, output flat
  • Accountable, but can't staff it
  • Output the team won't trust
VP Engineering

You run the teams that have to ship

…but right now
  • Seniors buried in review
  • Routine work clogs every sprint
  • AI help no one quite trusts
Digital Director

You carry the AI mandate alone

…but right now
  • Pilots, never production
  • You're the whole AI team
  • Momentum stalls without you

Three signs. Plenty of ambition, never enough hands.

If even one of these is your week, the rest of this page is the team you've been missing.

Aitonomy Control

One system to deploy agents, govern them, and measure success.

Aitonomy Control provides a system of autonomous AI agents. Define roles, set permission boundaries, and monitor all agent operations from a single dashboard.

Aitonomy ControlEU-sovereign environment
Your team
6 agents · 5 live
Control, around the whole team
Context 81% mappedAudit full trail · EUModels auto-routedSpend 7.3k/wk ▼Scaling liveConnectors 40+

EU-sovereign, enterprise-ready, with governance built in.

EU-sovereign
Stays in the EU
EU providers, not EU regions
Enterprise
Enterprise-ready
SSO & RBAC, BYOK, audit
Compliance
AI-Act ready
Governed by construction
Control
You set the gates
Stop where you say
How we work

We onboard agents
onto your team.

An embedded engineer of ours works inside your team and gets your agents earning trust on real work, then steps back as your team takes over.

01

Scan

2 to 5 days

We map your workflows and find which ones agents can take on.

02

Onboard

2 to 4 weeks

An engineer deploys your agents within your infrastructure.

03

Earn trust

4 to 6 weeks

Agents prove themselves before running autonomously.

04

Grow

Ongoing

Agents keep improving as your team takes full ownership.

How we measure success

Proof it's working

Track real adoption, measurable delivery shifts, and true bottom-line value.

Adoption
62%
of real work taken on by agents
  • active agents per team
  • coverage, per workflow
Impact
900hrs
back per team each quarter
  • throughput on agents
  • engineering time back
Value
20x
return on agent spend
  • cost per change down
  • rework and defects down
Illustrative figures, the kind your own instance reports, per workflow.
You might be wondering

Your questions answered.

The questions you would ask any new hire, answered for your agents.

We already use Copilot and Cursor. How is this different?+
Those tools help one developer type faster, then wait for a human. Expert agents are teammates, not autocomplete: each takes a specific task and runs it end to end, not just the part after the code is written. They start where trust is easiest to earn, reviewing pull requests, keeping docs up to date, and resolving bugs, then take on small features from the backlog and grow into more as they prove themselves. Each owns its task and answers for the outcome. Keep Copilot if your developers like it; the agents pick up the work around it.
Why not build this ourselves on Claude or GPT?+
You can, and a prototype is easy. The hard part is everything it takes to turn a model into a teammate you can trust: training it on your stack, keeping its skills and the law current, setting what it can touch and spend, a safe place to run, evals on every change, and the monitoring to scale it. Running that standing system is the real work. We do it, so your engineers build your product, not an agent platform.
Is it safe to put agents in our codebase?+
As safe as any new hire, and far more contained. Each agent starts with narrow access and earns autonomy on real work, one level at a time, the way you would grow a junior into more responsibility. It touches only what you allow, stops for a human at every gate you set, and logs every action. Nothing reaches production without the approvals you define.
Where does our code and data live?+
On EU-sovereign infrastructure: EU providers, not just EU regions. Your code and data stay in the EU, with a full audit trail you can hand to a regulator. Governance is built in for the laws that matter when you run AI on your codebase: GDPR for personal data, and the EU AI Act as its obligations phase in through 2026 and beyond. We track this landscape continuously, including what's still coming, and keep your setup compliant as the rules change.
What happens if an agent gets it wrong?+
Much the same as when any teammate makes a mistake, except the blast radius stays small by design: narrow scope, human gates on risky actions, and a complete record of every call and change. You see what happened, roll it back, and tighten the policy. Trust is earned level by level, the way it is with any new teammate, never granted up front.
See all questions →
A team of expert agentsExpert agents

Meet your team of
expert agents.

A fixed-price scan shows where agents start,
and the time your team gets back.