Case study AI knowledge assistant · Research

Khurshid Answers scholarly AI

An AI assistant that answers questions from the writings of Prof. Khurshid Ahmad — every answer linked to the book, page and passage it came from. Built for the Institute of Policy Studies, Islamabad.

4 languagesEnglish, Urdu, Arabic, Roman Urdu
Citedbook, page & excerpt
Read aloudwith sentence highlighting
Khurshid Answers featured chats on desktop and mobile
Client
Institute of Policy Studies, Islamabad
Industry
Research & knowledge preservation
We built
Reader app, admin console & API
Core technology
React · Node.js · MongoDB · AI speech
  • 720+commits in eight months
  • 86API routes
  • 13admin tools
  • 4languages for questions

See it livekhurshidanswers.org Chat app

The brief

The problem to solve

Professor Khurshid Ahmad’s writing on economics, governance and Islamic thought runs to more than 100,000 pages. IPS wanted students, researchers and journalists to be able to question it directly, in their own language — and to check every answer against the source.

Built forStudents & researchersJournalists & analystsEditors & reviewersIPS admins

Objectives

  1. Answer from his works — and only his works
  2. Show the book, page and passage behind every answer
  3. Take questions in English, Urdu, Arabic and Roman Urdu
  4. Let editors grow the library without a developer
  5. Make answers easy to listen to and share
What we built

Readers and librarians

Readers ask and listen; IPS’s editors and reviewers decide what the assistant knows.

Khurshid Answers — featured chats
  • Cited answersEach answer shows the book, page and excerpt it came from.
  • Follow-up questionsSuggested next questions to go deeper.
  • Four languagesAsk in English, Urdu, Arabic or Roman Urdu — and translate any answer.
  • ListenAnswers read aloud with a waveform and sentence-by-sentence highlighting.
  • Public or privateChat as a guest, or sign in to keep chats private.
  • Featured & shared chatsCurated public chats, and links to share an answer.
Admin console

Library team

Editors and reviewers grow the library without a developer — every book is reviewed before the assistant learns from it.

6 core features
  • Book draftsEditors submit a book with around 30 metadata fields.
  • Review & approveReviewers accept or reject each draft before training.
  • Training jobsApproved books go for training, with job tracking and re-indexing.
  • Articles from WordPressNew articles on khurshidanswers.org arrive for approval.
  • Feedback loopLikes, dislikes and written feedback on every answer.
  • Users & rolesAdmins, editors and reviewers; block users; CSV export.
How it works

From a book to a cited answer

The library workflow and the reader’s question meet in one system.

STEP 01

Submit a book

An editor uploads it with its metadata.

STEP 02

Review

A reviewer approves it for the library.

STEP 03

Train & index

The AI server indexes it; the job is tracked to done.

STEP 04

Ask

A reader asks in English, Urdu, Arabic or Roman Urdu.

STEP 05

Answer with sources

The answer streams in with its book, page and excerpt.

Architecture

How the system fits together

The reader app streams answers from a Python AI server and saves every conversation to the Node.js API, which also runs the library workflow and speech.

Apps
Reader appReact · Vite · English & Urdu
Admin consoleReact · TanStack Table
WordPress sitekhurshidanswers.org — articles & embed
Server
APINode.js · Express · TypeScript — users, conversations, library workflow and speech
Data & services
DatabaseMongoDB
AI serverPython — retrieval and answers
SpeechAI text-to-speech with word timestamps
Challenges

Getting it right

01

Trust in every answer

ChallengeA scholar’s words can’t be paraphrased into something he never said.

How we solved itAnswers carry the exact book, page and excerpt, so readers can check them.

02

A growing library

ChallengeNew books and articles keep arriving.

How we solved itA draft → review → train → track workflow lets editors add content without a developer.

03

Listening, not just reading

ChallengeMany readers prefer to listen — in English or Urdu.

How we solved itText-to-speech with word timestamps highlights each sentence as it’s read.

04

Four languages

ChallengeQuestions arrive in English, Urdu, Arabic and Roman Urdu.

How we solved itA bilingual English/Urdu interface with right-to-left layout, and translation of any answer.

Technology

The stack

Proven, well-supported tools — chosen so the platform is easy to run and to extend.

  • ReactReader app & admin
  • TypeScriptWeb, admin & API
  • ViteBuild
  • Tailwind CSSStyling
  • Node.jsAPI
  • ExpressAPI framework
  • MongoDBDatabase
  • PythonAI server
  • OpenAISpeech & timestamps
  • Google GeminiApp speech
The latest

Preserving knowledge with AI

Libraries and institutes are turning their collections into assistants people can question. The hard part is keeping every answer traceable.

Standard now

What’s changed — and how we use it

  • Source-first answers

    Every reply carries its citation.

  • Human-curated library

    Reviewers decide what the AI learns.

  • Multilingual by default

    English, Urdu, Arabic and Roman Urdu.

  • Listenable

    Natural read-aloud with highlighting.

  • Embeddable

    The chat drops into the institute’s own website.

Also in production: we build AI assistants over books, legal texts and company knowledge — see Pakistan LawBot.

Let’s talk

Have a library, archive or knowledge base people should be able to ask?

Tell us who will use it and what it must do. We’ll map the first release, the stack and the right team — in a free 30-minute strategy call.