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RAG knowledge search

Ask questions of your policies, circulars and manuals, and get answers grounded in your own documents, with a citation behind every one.

Overview

The answer existed, but finding it took days.

Years of circulars, amendments and manuals, spread across folders and formats. Sumato's retrieval-augmented generation (RAG) search reads them all and answers questions in plain language. Every answer points to the exact page it came from, so people can trust it and verify it.

  • Answers, not links

    Get a direct answer in plain language instead of a list of files to open.

  • Every answer cited

    Each response links to the source document and page, so it can be checked.

  • Always current

    New circulars are indexed as they are published, and superseded rules are flagged.

  • Regional languages

    Ask in English, Hindi, Assamese or Bengali and search across all of them.

Capabilities

Search built for documents that matter

Designed for policy, legal and procedural content, where a confident wrong answer is worse than no answer.

  • Hybrid retrieval

    Combines semantic and keyword search, so exact clause numbers and loosely worded questions both work.

  • Source citations

    Highlights the passage that supports each answer and links straight to it.

  • OCR for scanned files

    Old scanned circulars and gazettes become searchable text, including tables.

  • Version awareness

    Understands amendments and tells you when a newer rule supersedes an older one.

  • Guardrails

    Says "not found in your documents" rather than inventing an answer.

  • Access-aware results

    People only see answers drawn from documents they are allowed to read.

How it works

How an answer is built

  1. 01

    Documents are ingested

    PDFs, scans and web pages are cleaned, split into passages and indexed.

  2. 02

    A question is asked

    The question is matched against the index using meaning as well as keywords.

  3. 03

    Passages are retrieved

    The most relevant passages, and their versions, are selected and ranked.

  4. 04

    A cited answer is generated

    The language model answers only from those passages and cites each one.

Use cases

Where it makes a difference

  • Policy and rules desks

    Give officials instant, verifiable answers on service rules and procedures.

    • Service and leave rules
    • Financial delegation limits
    • Procurement procedures
  • Citizen helpdesks

    Help front-line staff answer scheme eligibility questions correctly the first time.

    • Scheme eligibility checks
    • Required document lists
    • Grievance status guidance
  • Compliance teams

    Find every obligation across contracts and regulations in seconds.

    • Regulatory clause lookup
    • Contract obligation search
    • Audit evidence retrieval

Results

Measurable results

  • 10,000+

    pages made instantly answerable for one institution

  • Seconds

    to find the right clause, compared with hours

  • 100%

    of answers linked to a source passage

Indicative figures from Sumato deployments. Outcomes depend on data, scale and adoption.

FAQ

Frequently asked questions

What is retrieval-augmented generation?

RAG first retrieves the passages from your own documents that are relevant to a question, then asks a language model to answer using only those passages. This keeps answers grounded and citable.

What happens if the answer isn't in our documents?

The system says so clearly. It is configured to decline rather than guess when it can't find supporting evidence.

Can it handle scanned and old documents?

Yes. Scanned PDFs and images go through OCR, including Indic scripts, before they are indexed.

Is our data used to train public models?

No. Your documents stay in your deployment and are never used to train third-party models.

Take the next step

Tell us about the problem in front of you. A Sumato solution architect will walk you through a live demo and an honest view of what it takes to solve it.