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Data & AI Fixed scope

Retrieval Chatbot on Your Documents

A grounded assistant that answers from your own manuals and policies, cites its sources and says when it does not know.

Delivered in

22 working days

Revisions

One round, included

Ownership

Yours from day one

Overview

What this engagement is

General-purpose chatbots invent answers about your business because they have never seen your documents. This builds a retrieval-augmented assistant over content you supply: policies, product manuals, support articles, contracts. Documents are chunked and embedded into a vector store, retrieval is tuned against a question set you approve, and every answer carries a citation back to the source paragraph. When the documents do not contain an answer, the assistant says so. We measure that behaviour before handover rather than assuming it.

Deliverables

What lands in your repositories

7 items
  • Ingestion pipeline for PDF, Word, HTML and Confluence content
  • Vector store with chunking and embeddings tuned to your document style
  • Retrieval and answer service with citations on every response
  • Web chat widget or Slack bot, whichever you prefer
  • Evaluation set of 50 questions with measured accuracy before and after tuning
  • Guardrails for out-of-scope questions and prompt injection attempts
  • Cost model showing expected monthly spend at your query volume

Outcomes

What changes once it ships

Answers grounded in your documents with a citation to check

Support load drops on the questions that repeat most

An honest accuracy number instead of a demo that impressed once

Process

How the 4 stages run

  1. 01

    Collect

    documents are gathered, deduplicated and cleaned

  2. 02

    Build

    ingestion, retrieval and answer generation are implemented

  3. 03

    Evaluate

    answers scored against your question set and retrieval is tuned

  4. 04

    Deploy

    release to a pilot group, then wider once accuracy holds

Booked most often by

  • Support teams answering the same policy questions repeatedly
  • Companies with large internal documentation nobody can search
  • Products where onboarding depends on reading a long manual

What we need from you

  • The document set, and clarity on which versions are current
  • 50 real questions your users ask, with the correct answers
  • A decision on which model provider you are comfortable using

These are collected in the technical brief that opens in your dashboard the moment payment clears. The clock starts when they arrive, not before.

Answers

Questions this engagement raises

Retrieval grounding and refusal behaviour reduce it substantially, and we measure it. We do not claim it reaches zero, because that would not be true.

No. We use providers with no-training terms, or a self-hosted model if your policy requires it.

Typically ₹3,000 to ₹15,000 a month depending on query volume. We model it for your numbers before you commit.

This is engineering work, not a physical product — nothing ships and there is no stock to run out of. Delivery is to the working days stated above, into systems you control, and the refund terms set out what happens if we miss the date.

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Capacity open this month

Read the scope. Know the price. Start on Monday.

No discovery calls to find out a number, no statements of work that take three weeks to sign. Pick the engagement that matches the problem and we assign the engineers.

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