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PRANJUL RATHOUR
PRANJUL RATHOUR

Posted on Originally published at pranjulrathour.scult.in

Choosing a final-year AI project that a recruiter will care about

#finalyearproject #ai #students #career

A final-year project is the one time college gives you months to build something and a panel that has to listen. Most students spend it on a chatbot with no users and a report with no numbers. Here is how I would choose, having reviewed many and having built the projects that got me hired.

Choose by user, not by technology

Start with a person who has a problem you can reach: a department, a local shop, an NGO, a clinic. The college-documents RAG project is a strong default because the users are in the building. A project with ten real users survives any viva question about relevance.

Pick one hard part

Retrieval quality, deterministic extraction, on-device inference, evaluation in a regional language — one genuinely difficult problem you will actually solve. The rest of the system should be plain engineering. Examiners and recruiters both look for the hard part; see the ideas in multimodal LLMs: five student project ideas.

Plan the evaluation in month one

  • A test set with known answers, built before the system works.
  • Metrics that fit: recall and faithfulness for retrieval, field accuracy for extraction, error rates per group for recognition.
  • A baseline to compare against — the naive version, or the tool users have today.

Scope for a demo

One demo path that runs live on the examiner's input. Everything else in the report as future work. A narrow, working system with numbers beats a broad architecture diagram every time, at a viva and at an interview.

Document as you go

  • A README that a recruiter can read in three minutes — see a GitHub profile recruiters actually read.
  • Weekly notes on decisions and failures; they become the report's best chapter.
  • A short demo video for people who cannot run it.

Done this way, the final-year project is the first item on your resume and the story you tell in every interview. Done the usual way, it is a PDF nobody opens again. The difference is decided in the first month.

About Pranjul Rathour

Pranjul Rathour, GenAI engineer from Kanpur, in a white turtleneck and black jacket, looking to the side
Pranjul Rathour — GenAI engineer, Kanpur

Pranjul Rathour speaking into a microphone on stage at a MeetKats event
Speaking at a MeetKats event

Pranjul Rathour holding a microphone while answering a question during a session
Taking questions during a session

Pranjul Rathour in a grey suit at Dr. Virendra Swarup Institute of Computer Studies (VSICS), Kanpur
At VSICS, Kanpur

Pranjul Rathour in front of an Integral Startup Foundation hackathon backdrop
At an Integral Startup Foundation hackathon

Pranjul Rathour is a GenAI engineer from Kanpur, India, and CTO at SCULT INDIA, currently shipping production RAG,
fine-tuning and agentic AI systems, mentoring 200+ students through TechVerse Enclave, and judging and speaking at
student hackathons across India. Updated 2026-09-07.

Reach out if you want to talk GenAI, book a campus session, or invite him to judge:

Pranjul Rathour · GenAI engineer, 3x hackathon winner, campus mentor. Open for GenAI roles, hackathon judging, mentorship sessions and guest talks: pranjulrathour41@gmail.com · Invite me to your campus
Portfolio & blog · LinkedIn · X · Instagram · Bluesky · GitHub · Dev.to

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