AI that survivescontact withreal users.
From prototype to production
A demo takes an afternoon. The skill starts where the thing runs every day against real, messy data, fails safely, and can be measured - so you find out it has degraded before your customers do.
Write to usThis fits if
- A pilot works in the demo and falls over on real data.
- You need answers grounded in your own documents, not the open internet.
- A repetitive workflow needs a human decision at one step and automation everywhere else.
- You have no way of telling whether the output is getting better or worse.
What is included
Retrieval over your own data
Your documents, tickets and records made searchable by meaning, with the plumbing that keeps them current.
Agents and workflow automation
Tools the model can call and act on, with the boring parts done properly: retries, limits, audit trails.
Evaluation and guardrails
An evaluation set built from your real examples, so “better” is a number. Human review wherever being wrong is expensive.
Integration and running it
Into the systems your team already uses, with monitoring, cost controls and a named person who answers.
What you get
- A working feature in production
- An evaluation set and its scores
- Cost and quality monitoring
- Documentation and handover
- Source code in your own repository
What we work with
- Claude · OpenAI · open-weight models
- RAG & vector search (pgvector, Qdrant)
- Python · TypeScript
- MCP · agent tooling
- Evaluation & tracing
- Self-hosting for sensitive data
- Observability & cost controls
- GDPR-compliant data flows
Tools are chosen to fit the problem, not the other way round.
AI implementation
Questions about this service
What does it cost to run each month?
It depends on volume, and we estimate it before building. We measure cost per call from day one, and it often falls once we move to a smaller model wherever the large one is not needed.
Can it run on our own infrastructure?
Yes. For sensitive data we use open-weight models on infrastructure you control. It costs more and usually performs slightly worse - we will tell you whether the trade is worth it.
How will we know if quality drops?
The evaluation set runs after every change and the scores are visible. Models shift and data shifts - without measurement it is your customers who notice, not you.
Sound like your situation?
Write us a couple of sentences and we will tell you whether we can help.