AI & machine learning

RAG development

Retrieval-augmented generation (RAG) lets AI look up answers in your knowledge base before responding, so it gives accurate, sourced answers instead of guessing.

What we offer

How we help

Knowledge base setup

Index documents, wikis, PDFs and databases securely.

Semantic search

Find information by meaning, not just keywords.

Cited answers

Every answer links back to its source.

Access controls

Users only see answers from data they're allowed to access.

How we work

From idea to launch in four steps

  1. 01

    Discover

    A free call to understand your goals. Within days you get a written scope, timeline and fixed quote.

  2. 02

    Design

    Clickable prototypes you can try before we build, so you know exactly what you're getting.

  3. 03

    Build

    Two-week sprints with a live demo every week. You see progress, not status reports.

  4. 04

    Launch & support

    We deploy, monitor and keep improving. Free bug fixes for 90 days after launch.

Technology

Tools we use

  • LangChain
  • LlamaIndex
  • pgvector
  • Pinecone
  • Claude

FAQ

Common questions

Is our data safe when we use AI?

Yes. We use providers and settings that don't train on your data, keep sensitive information under your control, and review privacy before launch.

How quickly can we see results?

Most AI projects start with a 2 to 4 week proof of concept, so you see real results before committing to a full build.

Let's talk about your rag project.

Free consultation and a fixed quote within 48 hours.

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Tell us about your project

We'll reply within one business day with next steps and a free estimate.