North India

RAG & Knowledge Retrieval across Rajasthan

Retrieval-augmented generation over your own documents, with citations, access control and measured answer quality. Covering every district and PIN code in Rajasthan.

Districts
32
PIN codes
992
Cities mapped
29

RAG & Knowledge Retrieval in Rajasthan

Your documents do not arrive as clean markdown. They are scanned PDFs, merged cells, ten-year-old templates. The ingestion pipeline is most of the work, and we build it for the corpus you actually have.

Rajasthan runs on mining and minerals, tourism, textiles, cement, handicrafts and solar energy, mining and utility-scale solar, where asset monitoring and field-data capture are the recurring problems. Where rag & knowledge retrieval earns its budget here usually follows directly from that mix.

We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong. Six weeks to something running in production, not six quarters to a strategy document.

नमस्ते , Namaste. We work in Hindi and English across Rajasthan.

Rajasthan coverage

State / UT
Rajasthan
Region
North India
Districts covered
32
PIN codes covered
992
Cities mapped
29
Working languages
Hindi, English

What is included

  • Ingestion pipeline for your real document formats
  • Chunking and embedding strategy tuned to your corpus
  • Hybrid keyword plus vector retrieval with reranking
  • Citations on every answer, traceable to the source page
  • Permission-aware retrieval that respects existing access rules
  • Retrieval quality benchmarked against a labelled question set

Questions

Do you cover all of Rajasthan?

Yes, all 32 districts and 992 PIN codes. Delivery is remote-first, so coverage is genuinely statewide rather than limited to the cities we happen to have offices in.

Which Rajasthan sectors do you work with most?

Across Rajasthan the economy leans towards mining and minerals, tourism, textiles, cement, handicrafts, solar energy. Mining and utility-scale solar, where asset monitoring and field-data capture are the recurring problems.

RAG or fine-tuning?

RAG for knowledge that changes and must be cited; fine-tuning for style, format and task behaviour. Most production systems use RAG for the facts and light fine-tuning or few-shot prompting for the form.

How accurate will it be?

We build a labelled question set from your domain and report retrieval precision and answer accuracy against it. That number is the deliverable. We do not ship a system whose quality nobody has measured.

Can it respect our existing permissions?

Yes. Retrieval is filtered by the user's actual entitlements, so the assistant can never surface a document the user could not already open.

RAG & Knowledge Retrieval in Rajasthan

Covering all 32 districts. Tell us what you are trying to change.

Or email bd@dtrasglobal.com · call +91 74118 77878