Contact person: AI Answer Script Evaluator

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Location: Delhi, India

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I am building a system that lets me upload a PDF of a student’s handwritten answer script together with the model answer, then instantly returns an evaluated script complete with marks, question-level comments, and an overall summary. The core is an AI engine that must read handwriting (robust OCR), compare each response with the supplied model answer using natural-language techniques, gauge overall content quality, and pinpoint the gaps so the student knows exactly how to turn the same paper into a “topper-level” submission next time.

For feedback, I need a blend of granular insights and a concise overview: per-question marks and commentary plus a dashboard-style summary sheet. The AI should flag where relevance dropped, where depth was missing, and suggest concrete improvements.

The results must flow into a mobile application that runs smoothly on both iOS and Android. A single codebase (Flutter, React Native, or similar) is fine as long as performance remains high and native PDF annotation is supported.

Deliverables
• Cloud-ready AI backend with an endpoint that accepts the student PDF + model answer and returns JSON with marks, comments, and an annotated PDF.
• Cross-platform mobile app that lets me upload the documents, view/download the marked script, and share the summary report.
• Admin interface (web or in-app) to feed model answers, set marking schemes, and edit AI feedback if necessary.
• Developer-level documentation and a brief test plan so I can verify accuracy and iterate on the marking rubric.

If you have prior experience combining OCR, NLP, and cross-platform mobile builds, I’d love to see a quick outline of how you would approach handwriting recognition accuracy, relevance scoring, and the feedback generator." (client-provided description)