Services
Production-ready AI applications
Between an impressive prototype and an application that carries daily business lie error handling, permissions, monitoring and cost per request. That stretch is exactly what we build with you.
The prototype is not half the job
A prototype has to work once, under observation, with clean inputs. A production application has to work a thousand times, unobserved, with the inputs real people actually produce — truncated uploads, empty fields, three requests at once, the third-party system momentarily offline. That stretch is not the second half of the project, it is the larger part.
So the question that decides success is not “does the demo run” but “what happens when something goes wrong”.
Structured outputs beat the bigger model
A model that returns free text forces the downstream software to guess. A model that must fill a fixed schema can be checked: a required field missing, a value outside the permitted range, a type mismatch — validation catches it before anything is stored. That is usually more effective than reaching for the next larger model.
A controlled failure beats a confident wrong answer. Systems not allowed to say “I don’t know” produce inventions instead.
What has to be in place before go-live
- Monitoring of quality, latency, error rate and cost per request — LLM calls are the one item that scales linearly with usage.
- Regression tests against a fixed test set. Changing a model or a prompt is a deployment and deserves the same scrutiny.
- Permission and tenant separation down to the data layer, not just in the interface.
- A fallback path: what does the application show when the model provider is not responding.
From MVP to rollout without discarding the architecture
An MVP should be fast but not arbitrary. From the start we keep three things cleanly separated: the connection to the model provider, the business logic and the interface. That keeps switching providers a matter of configuration rather than a rebuild — and it is needed regularly in this field, because prices and capabilities change faster than your own business logic.
How we support you
- Full technical ownership from architecture through implementation and code review to a productive go-live.
- React and TypeScript frontends, secured REST APIs, background workers, PostgreSQL data modelling.
- Provider-agnostic abstraction layer, so switching provider does not trigger a rewrite.
- Cloud deployment with Docker, CI/CD, logging and monitoring — including handover to your team.