AI Solutions
RAG assistants that answer from your own data, with sources
Sound familiar?
Answers buried in a thousand files
Policies, manuals, contracts and old emails hold the knowledge, but search returns file names instead of answers. New hires ask the same questions and senior staff keep interrupting their work to reply.
Chatbots that make things up
A generic model sounds confident and gets your refund policy wrong. Without retrieval and citations, every answer is a liability and nobody in the company trusts the tool enough to rely on it.
Stale knowledge nobody re-indexes
The pilot was trained on last year's documents. Nobody owns the update job, so the assistant quietly drifts from reality while the team assumes it is current.
What you get
- Document ingestion pipeline
- Chunking and embedding strategy
- Vector search with metadata filters
- Grounded answers with citations
- Streaming chat interface
- Permission-aware retrieval
- Evaluation set and accuracy report
- Scheduled re-indexing jobs
Stack and tools
- Claude API
- OpenAI embeddings
- pgvector
- Pinecone
- Qdrant
- LangChain
- Vercel AI SDK
- Next.js
- Node.js
- PostgreSQL
- Redis
How we do it
- 1
Collect and clean
We connect your sources (drives, wikis, databases, ticketing tools), normalize the content, and decide what should and should not be retrievable based on who will ask.
- 2
Index
Documents are chunked with their structure preserved, embedded, and stored with metadata so retrieval can filter by product, customer, date or access level before ranking.
- 3
Ground and test
The assistant answers only from retrieved context and cites it. We build an evaluation set of real questions and measure answer accuracy and citation precision before launch.
- 4
Launch and keep fresh
The interface streams answers in your web app, Slack or Teams. Re-indexing runs on a schedule or on change events, and a usage dashboard shows what people ask and where answers miss.
Starting at
from $6,000
Typical timeline 3 weeks. Up to three data sources and one interface in the first release.
Related work
RAG Assistants: questions people ask
Further reading
Let's scope your rag assistants project.
Tell us what you are building or what is slowing you down. We reply within one business day.