Xponentiate

Problem

Healthcare recruitment in India involves high-volume screening across multiple roles and locations. Recruiters manually review hundreds of resumes, write job descriptions from scratch for each role, and track candidates across spreadsheets. The process is slow, inconsistent, and doesn't scale for a venture studio launching multiple healthcare companies simultaneously.

Solution

Xponentiate is an AI-powered recruitment platform built for a healthcare venture studio. It automates resume screening, generates role-specific job descriptions from templates, and manages the full candidate pipeline from application to offer.

Key Technical Decisions

Turbo monorepo — The platform has a Next.js frontend, FastAPI backend, and shared TypeScript types. Turbo ensures the frontend and backend stay in sync during development, with incremental builds that only rebuild what changed. For a two-person team, this eliminated the "works on my machine" class of bugs.

Alembic for database migrations — Healthcare recruitment involves evolving data models (new compliance fields, changing role taxonomies). Alembic provides version-controlled, reversible schema migrations that run in CI/CD. Every database change is auditable — important for a platform handling personal candidate data.

AI screening with human override — The AI ranks candidates but never auto-rejects. Every candidate flagged as low-match is still visible to recruiters with the AI's reasoning. This design was non-negotiable for the client — healthcare recruitment has legal implications that require human decision-making in the loop.

Impact

• Production platform serving a healthcare venture studio
• AI-powered resume screening reducing initial review time by 70%
• JD generation from role templates with customization per location and seniority
• Full candidate pipeline from application to offer in a single platform
• Human-in-the-loop design ensuring compliance with hiring regulations