RAG engineering from Minden

We take RAG to production

Many AI projects stay a demo. We build AI systems that run in production, with a focus on RAG.

Explore the RAG Workshop or book a consultation

What we work with

Microsoft, open source, or something of your own.

Azure AI Search

Microsoft Copilot

Microsoft Fabric

Vespa.ai

Qdrant

pgvector

Chroma

Your stack

01 · The Problem

Every day your employees search for knowledge & can't find it fast enough.

Contracts, policies, tickets, emails: it all exists, but spread across SharePoint, file servers, CRM, and half a dozen tools. What you need right now, you still can't find.

ChatGPT barely helps: it doesn't know your internal documents and often isn't allowed to see them for compliance reasons. And low-code builders break the moment things get serious.

The answer is Retrieval Augmented Generation (short: RAG): an AI-based method that looks things up in your own documents and gives sourced answers.
But few RAG prototypes make it from test to real operation. That's exactly our work.

02 · Our Services

From workshop to a functioning AI application.

RAG Workshop

From zero to RAG prototype in three days.

Evolutionary, from naive to modular RAG: hybrid search, reranking, evaluation with Ragas. You build it yourself and learn to weigh stacks neutrally.

3 daysUp to 10 participants

View workshop

AI Agents & RAG Delivery

We built our own RAG architecture.

That's why we master any stack: Microsoft (Copilot, Azure AI Search, Fabric), ready-made platforms (Vespa.ai, Qdrant …) or fully tailored. Connector system, chunking, RBAC, model- and infrastructure-agnostic.

On-PremiseCloudHybrid

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