Which AI models do you use?

Whichever fits the job. We work with all the major providers and design the architecture to keep you vendor-independent, so switching to a better or cheaper model later is a configuration change, not a rebuild.

What happens with our data?

It stays yours. We design for privacy from the start: PDPL-aware architecture, provider agreements that exclude training on your data, and on-premise options when the data can't leave your infrastructure.

How do you handle hallucinations?

Grounding on your real data, structured outputs, and eval suites that measure wrong answers on your actual cases, plus interface design that shows sources. Zero hallucination isn't achievable; measured and managed is.

What we build · AI products

AI features built for real users.

Assistants, automation, and AI-powered features, built by a team that works with these tools every day.

Evals from day oneCost-controlledNo vendor lock-inFull source ownership

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How we build with AI

Validate the use case

First question: does this actually need AI? If simpler technology does the job, we'll say so. The AI features worth building are the ones where a model does something rules never could.

Prototype against real data

A working prototype on your actual data in the first week. The only way to know an AI feature works is to run it against the real thing.

Build with evals

Every prompt and pipeline gets an eval suite: measurable pass/fail on real cases. When a model or prompt changes, you know within minutes whether quality dropped.

Guardrails and fallbacks

Cost caps, rate limits, content moderation, and graceful failure when a model is down or wrong. Reliability is designed in from the start.

Ship and monitor

Deployed with usage and quality dashboards, so you can see what it costs, what users ask, and where it needs improvement.

What you get

Working AI feature, assistant, or automation
Eval suite with real test cases
Cost monitoring and hard spending caps
Fallback behavior for model failures
Usage and quality dashboard
Full source code and documentation

What we work with

All major AI model providersRetrieval and search over your dataAutomation and agent pipelinesEvals and quality monitoringCloud or on-premiseYour data stays yours

Good to know

Does it actually need AI?

Some requested AI features are better served by a plain database query: cheaper, faster, and always accurate. We assess your use case in the first week and tell you which approach genuinely fits, before you pay for a build.