From a hypothesis to a system in production.
We do not sell “AI”. We take a concrete problem in your company, check whether a model solves it better than what happens today, and if it does we build it inside the systems you already use.
How the work goes
Discovery
Processes, available data, constraints. You come out with a use case and an estimate.
Prototype
A working prototype on your real data, measured against real cases.
Integration
Inside the ERP, the CRM or the platform: permissions, logs, human control.
Evolution
Quality monitoring, swapping models, new use cases.
What we do
06 servicesLLM integration
Rails, Python, Go, Node: your stack stays. We add language models through an API or on-premise, with tool-calling against your data and caching to keep costs predictable.
DetailsRAG and knowledge base
Ingesting documents, manuals and tickets. Hybrid search, answers with cited sources, permissions inherited from the systems of record.
DetailsProcess automation
Agents that classify, extract, route and reply. Every action logged; human approval wherever the risk calls for it.
DetailsAI-first MVP
For startups and new business lines: a working product in a few weeks, with AI as the foundation.
DetailsMCP servers
The Model Context Protocol is the open standard an AI assistant uses to talk to external software. We expose ERPs, databases and APIs as MCP servers: you write the tools once and any compatible client can use them, with the permissions you decide, without redoing the integration for every model.
DetailsFractional AI/CTO
Choosing models and vendors, architecture, data security, growing the team. A few days a month, for companies that need technical direction and not a CTO to hire.
DetailsTell us the process. We will tell you if it makes sense.
A free 30-minute call, with no commercial follow-up unless you want it.