Autonomous AI agents
An agent works inside your email, Slack, CRM, ERP, or internal apps. Written rules define what it can do alone and what waits for your approval.
Explore AI agents →For the work your business actually does
AI agents and custom software for small and mid-sized businesses, shipped in weeks
Built with engineering discipline: a written specification, tests, code review, continuous integration, and maintenance. You approve the scope and the result.
Build the tool. Or put an agent to work.
For owners, operations leaders, and IT leads who need less manual work and a clear view of what runs their business.
Custom business software
Replace spreadsheets and email threads with an application built around your workflow. AI helps write the code; an engineer owns the result.
Explore custom software →What we build
AI agents and custom software, by service, by industry, and the guides behind our decisions.
Services
Industries
How a project runs
A visible process from the first conversation to ongoing maintenance. You approve the scope and test the result before launch.
- 1
Discover
Walk through the workflow and define a useful first scope.
- 2
Specify
Write requirements, approval rules, and a sprint plan.
- 3
Build & verify
Test-first sprints, code review, and continuous integration.
- 4
Accept & launch
You test the preview and sign off before production.
- 5
Maintain
Monitor, fix problems, and plan the next improvements.
AI speeds up development. Discipline keeps it dependable.
AI-assisted development needs more than a good prompt. These checks protect the business process you rely on.
A written specification
You can review the scope, workflows, and acceptance criteria before implementation starts.
Tests before implementation
Important business rules become automated checks, so changes don’t silently break them.
An engineer reviews the code
AI output is checked for correctness, architecture, access controls, and maintainability.
Continuous integration
Each change runs through automated tests and build checks before it can be released.
Maintenance after launch
Monitoring and ongoing fixes keep the application or agent useful as your tools and needs change.
The first company we run with agents is our own.
Inside the operating model
Specialized roles. Shared tools. Human decisions.
See how agents handle growth, software products, operations, and quality—with short reports, recorded run statuses, and explicit approval boundaries.
Read the case study →A small studio you work with directly.
No account managers, no handoffs
Based in France, we work remotely with international clients. The senior engineer who scopes your project also builds it, reviews every change, and maintains it, supported by AI agents.
About the studio →Questions before we start
How much does it cost to develop an AI agent?
A single-task agent on your existing tools costs $2,000 to $4,500 to build, then $500 to $1,100 a month for supervision and maintenance, plus model usage and hosting. An agent built into a custom business application costs $10,000 to $30,000.
What an AI agent really costs →Can I develop an AI agent myself?
Yes: with Claude or ChatGPT and a few connectors, a capable non-developer can build a useful single-task agent. It is worth having it built when the agent touches customers, money or a system of record.
Claude for small business: the three levels →Let’s start with the process you want to improve.
Bring the spreadsheet, the workflow, or the idea. We’ll talk through what is worth building and where human approval belongs.