Ingest anything
PDFs, Word, spreadsheets, websites, Notion, Drive and databases — chunked, cleaned and embedded automatically.
AI & RAG Applications
Your knowledge,answering questions.
We turn manuals, policies, contracts and tickets into an assistant your team and customers can trust — grounded, cited and measurable.
Modules
- Document ingestion
- Hybrid search
- Chat with citations
- Admin & analytics
- Prompt manager
- Evaluation suite
- WhatsApp bot
Built with
- Claude
- OpenAI
- PostgreSQL
- pgvector
- NestJS
- Next.js
Capabilities
Everything a serious RAG system needs
Hybrid retrieval
pgvector semantic search fused with keyword ranking and metadata filters, so the right paragraph surfaces every time.
Grounded with citations
Every answer links back to its source passage. No source, no claim.
Guardrails & permissions
Row-level access, PII redaction and topic boundaries, so users only see what they are allowed to see.
Evaluated, not guessed
Golden-question test sets and answer scoring run on every change to prompts or models.
Fits your stack
REST APIs, WhatsApp, Slack, web widget or embedded inside your existing product.
How we deliver
From documents to a dependable assistant in weeks
- 01
Knowledge audit
Week 1We map sources, access rules and the 50 questions that matter most.
- 02
Pipeline & index
Weeks 2–3Ingestion, chunking strategy and hybrid search tuned on your data.
- 03
Assistant & guardrails
Weeks 3–4Chat UI, citations, permissions and safety boundaries.
- 04
Evaluate & launch
Week 5+Golden-set scoring, staff pilot, then production rollout with monitoring.
Frequently asked questions
RAG questions, answered
01Will our data be used to train AI models?
No. We use enterprise API terms where providers do not train on your data, and we can run open-weight models fully on your own servers when required.
02How accurate are the answers?
Answers are restricted to retrieved passages and cite them. We measure accuracy on a golden set of your real questions before launch and track it after.
03Can it run on-premise?
Yes. The full stack — database, vector index, application and optionally the model — can be deployed inside your network.
Live
Open live demo
Keep reading
Have a pile of documents nobody reads?
Send us a sample. We will show you a working prototype answering from it.