North India

RAG & Knowledge Retrieval across Punjab

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

Districts
22
PIN codes
527
Cities mapped
22

RAG & Knowledge Retrieval in Punjab

Permission-aware retrieval is not optional in an enterprise. If a user cannot open a document in SharePoint, the assistant must not quote it. We enforce that at the retrieval layer, not in the prompt.

Punjab runs on agriculture and agri-machinery, textiles and hosiery, sports goods, light engineering and food processing, agri supply chains and SME manufacturing, where the practical win is workflow automation rather than frontier models. 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. You own the code, the models where they are open-weight, and the documentation to run it without us.

ਸਤ ਸ੍ਰੀ ਅਕਾਲ , Sat Sri Akaal. We work in Punjabi and English across Punjab.

Punjab coverage

State / UT
Punjab
Region
North India
Districts covered
22
PIN codes covered
527
Cities mapped
22
Working languages
Punjabi, 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 Punjab?

Yes, all 22 districts and 527 PIN codes. Delivery is remote-first, so coverage is genuinely statewide rather than limited to the cities we happen to have offices in.

Which Punjab sectors do you work with most?

Across Punjab the economy leans towards agriculture and agri-machinery, textiles and hosiery, sports goods, light engineering, food processing. Agri supply chains and SME manufacturing, where the practical win is workflow automation rather than frontier models.

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 Punjab

Covering all 22 districts. Tell us what you are trying to change.

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