Built from an interview project.Expanded into a product.
HireSense AI began as a backend system for the SHL AI Research Intern assignment and evolved into a polished SaaS experience for conversational assessment intelligence.
Mission
Help hiring teams move from vague role requirements to grounded, explainable SHL assessment recommendations.
Problem
Assessment catalogs are deep, nuanced, and easy to misuse when recruiters have limited time or unclear requirements.
Solution
HireSense AI combines a premium conversational interface with a stateless backend, hybrid retrieval, and validated catalog-only outputs.
A clean separation between product UI and recommendation intelligence.
The frontend focuses on clarity, interaction quality, accessibility, and trust. The backend owns catalog scraping, embeddings, FAISS search, hybrid retrieval, decision policies, and validated response objects.
Stateless API
Every request carries full conversation history.
Grounded output
Recommendation objects are catalog-derived.
Typed frontend
Next.js, React, TypeScript, TailwindCSS.
Deployment-ready
Frontend and backend deploy independently.