01 · Retrieval
Private knowledge
Small, grounded search layers over internal documents — with citations, not confabulation.
We build focused AI tools for teams that prefer calm systems over noisy demos: retrieval, evaluation and automation that stay close to the data.
Small, grounded search layers over internal documents — with citations, not confabulation.
Task-specific eval harnesses that tell you when a model is actually better, and when it is not.
Deterministic workflows around the model: retries, guardrails, logs, and a human in the loop.
Current focus. A compact retrieval stack for engineering archives, running on a single node in Frankfurt. No dashboards for the sake of dashboards — just fast answers with a traceable path back to the source.
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