000 / JOURNAL
Notes du studio.
Comment nous menons les logiciels d'IA en production, et comment nous les y maintenons.
What make it autonomous actually means
A plain language look at the autonomy add on and how your app starts to sense, decide, and act on its own.
Lire →Where your software and your data live is your call
How we decide where your software and your data run, your cloud, ours, or a partner cloud, and why that choice and that control stay yours.
Lire →Shipping a SaaS end to end
Design, build, ship, and run a product on a modern stack. Why one team that also hosts what it builds beats a handoff between vendors.
Lire →How we turn an idea into a plan you can trust
A clear look at how we scope work honestly before anyone commits, so you know what you are getting and why.
Lire →How to choose a team to build your AI product
A calm buyer guide for founders and operators deciding who should build and run their AI software.
Lire →Secure agent access without losing sleep
Letting an AI assistant act through your tools is a real grant of power. Here is the security model that makes it safe: OAuth 2.1, DPoP, row level access, and a hash chained audit trail.
Lire →What you get when one team builds it and runs it
Why hiring a studio that both builds and operates your AI system beats a contractor who hands off a repo and disappears.
Lire →MCP servers are a button now. Here is what actually costs money.
Generators make the wrapper free. The work that decides whether your MCP server is safe and useful sits everywhere else.
Lire →Your AI pilot is stalled. Here is the path to production.
A calm walk through how we close the gap between an AI pilot that impressed everyone and a system that actually runs in production.
Lire →Why your AI pilot never reached production
A demo that wows a room is not a product. Here is the real distance between a prototype and production grade software, and how to close it.
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