Private document Q&A
[01]RAG over your PDFs, SOPs, and knowledge base with login and source citations.
AI Solutions
RAG, assistants, and LLM features that sit inside your product or internal tools.
RAG SystemsLLM FeaturesInternal AssistantsEvaluation Setup
Who this is for
Useful AI is narrow: answer from your documents, draft from your templates, or speed up a known workflow. We avoid broad chatbots that sound clever and fail in practice.
We can deploy privately or in the cloud, depending on whether the data can leave your network.
Common problems
3 Areas- 01
Teams want AI, but the documents and permissions are a mess.
- 02
Demo chatbots look fine until someone asks a real operational question.
- 03
Nobody measures answer quality, so trust erodes after the first wrong reply.
What we deliver
4 OfferingsProduct AI features
[02]Assistants and generation flows embedded in your existing web app.
Internal ops helpers
[03]Tools that draft, classify, or summarise work for support and operations teams.
Evaluation and guardrails
[04]Test sets, logging, and review so you know when answers drift.
Typical engagement
Timeline
A focused RAG or assistant pilot usually takes 4–10 weeks after data access is ready.
Budget
Focused pilots often start from ₹50,000 ($500). Broader RAG / product AI work commonly sits around ₹12–40 lakh ($15k–$50k). Private hosting costs more.
Working model
Pilot on a real document set, measure answer quality, then decide whether to expand.
What matters in delivery
- Clear data boundaries and login before model work
- Citations or review steps when answers affect decisions
- Local or cloud deployment based on security needs
- Ongoing evaluation instead of a one-time demo
How we work
- 01
Pick the use case
We choose one workflow with measurable value, not a vague “AI for everything” brief.
- 02
Prepare the data
Clean sources, access rules, and a small evaluation set of real questions.
- 03
Build and test
Ship a usable interface, then score answers with your team before wider rollout.
- 04
Operate and improve
Monitor failures, add documents, and tune prompts or retrieval as usage grows.
Related industries
Next step
Tell us the workflow or product you need. We will reply with an honest fit check, rough timeline, and budget band.
Book a Discovery Call ↗Related work
View portfolio →
Questions
Can this run on our own servers?
Yes, when the use case needs it. Local deployment costs more to set up, but keeps sensitive documents inside your environment.
Do we need a huge dataset to start?
No. A clean set of real documents and 30–50 example questions is enough for a useful pilot.
Will AI replace our team?
We build helpers for research, drafting, and lookup. Final decisions and approvals stay with people.
Need ai solutions for a live business problem? Start with a short discovery call.
Book a Discovery Call ↗