Zehaanat

Current-affairs reading that carries into revision and essay practice

Services: Document AI ; AI Workflow Automation ; RAG Knowledge Systems
Delivery: CSS/MPT preparation product across web and Android-first mobile.

These are implemented product details, not measured learning gains.

CSS preparation involves reading current affairs, selecting useful facts, connecting them to subjects, revising them, and using them in written answers.

The source material creates another difficulty. Ordinary articles contain fetchable text; ePaper pages can be images with page layout. The same extraction method does not handle both well.

Zehaanat fetches text articles server-side and accepts ePaper screenshots for vision-based extraction. GPT-5 nano turns the material into study-oriented content. A tagged factbook organizes it by subject and theme, then schedules repeated review.

The workspace also includes MPT drills, timed mocks, saved accuracy history, subject selection with official group constraints, study planning, and recovery scheduling.

Essay tools support PEEL outlines, drafts, heuristic checks, and AI feedback. Past-paper search has an optional RAG answering path. The Android-first React Native app shares API contracts with the web product.

Administrators manage access periods, module permissions, manual payments, and AI usage.

Handle page images separately from article text. Cheerio-based fetching prepares text sources; screenshot input supplies image-based material to the vision workflow.

Make revision part of the record. A saved fact has subject/theme context and a review schedule rather than remaining an isolated note.

Measure model use at the account level. The usage ledger records tokens, latency, failures, and estimated cost without retaining prompts or study content in that ledger.

Keep payment behavior explicit. Payments are verified outside the app, then recorded by an administrator to activate or renew access.

The delivered product connects source intake, study extraction, revision, practice, and writing. It also exposes the operational cost of its AI features to the administrator.

The repository documents desktop/mobile Playwright coverage and shared contracts for mobile. No pass-rate, student-count, or official examiner endorsement is claimed.

Next.js, MongoDB; OpenRouter and OpenAI; GPT-5 nano text/vision extraction and essay feedback; Cheerio; React Native and shared API contracts; Playwright; account-level AI limits and usage reporting.

Read the article. Keep the fact. Use it in an answer.
Zehaanat connects AI study extraction with a tagged factbook, spaced review, MPT practice, and essay feedback, with separate text and ePaper processing paths.

We built Zehaanat around the preparation routine. Text and ePaper sources become study material, facts enter scheduled revision, and students can use that material in practice and essays. The admin can also see what the AI usage costs.

Existing product screenshot. The displayed score is example AI feedback, not an official exam mark.