RAG development services · EonTech

Answers your team can
actually trust and cite.

We build RAG over your own documents. Each answer is grounded in your content, cites its source, and respects access rules. We test quality. Not assume it. Your knowledge, made usable and entirely yours.

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  • Grounded with citations
  • Access-aware retrieval
  • GDPR · ISO 27001
Your documents
Answers come from your data, not the open web
With citations
Every answer links back to its source
Access-aware
Retrieval filters by who can see what

Retrieval before generation

The model is only as good as what it reads

Most RAG projects fail at retrieval, not generation. We tune chunking, embeddings, and search until the right passage surfaces. Then we constrain the model to answer from it.

The result is grounded answers. Each one cites its source so you can check it. We measure faithfulness. We don't assume it.

See our data engineering practice

What we build

A full RAG stack over your knowledge

From messy source documents to governed, cited answers, we build every layer. We include testing that keeps it honest as your content grows.

  • Document ingestion

    Parsing, chunking, and cleaning across PDFs, wikis, tickets, and code. We handle messy real-world content, not just clean text.

  • Hybrid retrieval

    Vector search combines with keyword and metadata filters. The right passage surfaces even for part numbers and exact phrases.

  • Grounded generation

    Answers come only from fetched passages. Each gets inline citations you can open and check. No source, no claim.

  • Access control

    Retrieval filters by the user's permissions first. The model never sees a document the user may not access.

  • Evaluation pipeline

    Graded test sets measure faithfulness on every change. You know each update helped. No guessing.

  • Feedback loops

    Feedback collected in production and sent back to retrieval tuning and content fixes.

What you get

Grounded, governed, and measurable

  • Citation-first answers — every claim links to the passage it came from.
  • Permission-aware retrieval — the index never leaks across access lines.
  • Hybrid search — semantic plus keyword so exact terms are not lost.
  • Freshness pipelines — indexes re-sync as source documents change.
  • Faithfulness evals — answers graded against fetched context.
  • Owned infrastructure — the index, embeddings, and pipelines stay yours.

How we deliver

From scattered documents to trusted answers

We build retrieval first and prove faithfulness before we scale. You always know what the system can answer and how well.

  1. 01

    Map your knowledge

    We list the sources, their formats, and their access rules before any indexing. Garbage in is the failure mode we avoid.

  2. 02

    Build retrieval first

    Generation is only as good as what it retrieves. We tune chunking and embeddings until the right passages surface reliably.

  3. 03

    Ground and cite

    We constrain the model to answer from retrieved context. Each answer gets citations. We then grade faithfulness against a test set.

  4. 04

    Govern in production

    We wire in access control, monitoring, and feedback. The index stays fresh as your documents change.

Common questions

What knowledge teams ask first

  • How do you keep answers grounded in our content?

    The model answers only from passages in your documents. Every claim gets an inline citation you can check. A faithfulness test runs on each change to catch drift. No system removes hallucination fully. We reduce it and measure it.

  • Can it respect who is allowed to see which documents?

    Yes. Built in from the start. Retrieval filters by the user's permissions before generation runs. The model never sees a document you may not access. Access rules are a design input, not an afterthought.

  • Do we own the index and the pipelines?

    Always. The ingestion pipelines, embeddings, vector index, and test suites are yours to run and extend. We build on tools you control. No lock-in to any single model or vendor.

Make your knowledge answerable

Tell us where your knowledge lives and who needs to use it. We will scope a grounded, cited, access-aware first step in days.

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