Turn your company knowledge into accurate, cited answers.
Retrieval-augmented generation (RAG) lets AI answer from your own sources instead of guessing. We build RAG systems that handle messy real-world data such as PDFs, wikis, tickets, SharePoint, Confluence and databases, and we measure retrieval quality so answers stay grounded as your content grows.
RAG & Knowledge Systems
Data ingestion pipelines
Connectors, parsing, chunking and metadata enrichment for structured and unstructured sources.
Vector & hybrid search
Embeddings, keyword + semantic hybrid retrieval, re-ranking and permission-aware filtering.
Grounded answer generation
Answers with inline citations, confidence signals and graceful "I don’t know" behavior.
GraphRAG & agentic retrieval
Knowledge graphs and multi-step retrieval for complex, multi-hop questions.
Retrieval evaluation
Golden datasets and automated metrics for recall, faithfulness and answer relevance.
Enterprise access control
Row- and document-level security so users only see what they are allowed to see.
What you can expect
- Faster answers for support, sales and internal teams
- Fewer hallucinations through measured, grounded retrieval
- A knowledge platform that scales to millions of documents
Tools we use
We are vendor-neutral and choose tools to fit your stack, team and budget.
From first call to production.
- 1
Free consultation
A 30-minute call to understand your goals and constraints.
- 2
Proposal
A written scope, timeline and fixed price or monthly rate.
- 3
Delivery
Weekly demos and shared repositories, from day one.
- 4
Handover & support
Documentation, training and optional managed services.
Common questions
Which vector database should we use?
It depends on scale, latency and what you already run. Postgres with pgvector is often enough; we recommend managed vector stores when scale or features demand it.
Can RAG respect our existing permissions?
Yes. We sync access control lists from source systems and filter at retrieval time so restricted content never reaches the model.
How do you measure accuracy?
We build an evaluation set from real questions and track retrieval recall, answer faithfulness and relevance on every change.
AI & Generative AI Solutions
Custom LLM applications, copilots and AI features built into your product and workflows.
AI Agents & Automation
Autonomous and human-in-the-loop agents that use your tools to complete real business tasks.
MLOps & LLMOps
Pipelines, model registries, monitoring and serving infrastructure for reliable ML in production.
Let's talk about RAG.
Tell us what you are building. We will reply within one business day with next steps, and the first consultation is free.