AI-implementering

We don’t deploy and pray. Every workflow ships with a persistent eval harness — a fixed test set we run weekly to catch regressions. If quality drifts, we know before you do. For high-stakes outputs (legal, financial, medical) we add a human-in-the-loop gate by default.

Your data stays in your stack unless you opt otherwise. We use enterprise tiers (Claude on Anthropic, Azure OpenAI, AWS Bedrock) with zero-retention contracts. Sensitive workflows can run entirely on infrastructure you control. We sign DPAs.

Most engagements have something live in week 4 and a second workflow by week 10. The code is yours, the docs are yours, the eval set is yours. We can keep running it on a part-time retainer, or train your team and hand off — your call.

We don’t do strategy decks. The first deliverable is a working workflow in production. We pick one high-leverage use case, build it, evaluate it, then pick the next one — instead of mapping a 24-month roadmap that goes stale in 8.

AI implementation engagements start at €4,500 for a single workflow shipped end-to-end. Larger programmes (3+ workflows, custom apps, ongoing tuning) are scoped against expected savings or revenue, with a fixed delivery price.

Whatever fits the job. Claude for reasoning and writing, GPT for breadth, Llama / Qwen for cost-sensitive workloads, custom fine-tunes when the data warrants it. Model-agnostic by design — if a better one ships, you switch in a config change, not a rebuild.