Brief
A US-based SaaS founder needed a fully functional AI recruitment platform that could automate candidate screening, schedule interviews, and give hiring managers real-time scoring insights, all without building an in-house engineering team.
Background
The client had validated demand for an AI-powered hiring tool targeting mid-sized companies drowning in manual resume reviews. They had a clear product vision but no technical co-founder and limited runway to spend on traditional hiring. The platform needed to handle job posting management, resume parsing, intelligent candidate ranking, and automated communication workflows from a single interface. The goal was to launch an MVP fast enough to onboard pilot customers and raise their next funding round.
Challenges
Most existing ATS tools in the market were bloated with features that slowed hiring managers down rather than helping them move faster. The core challenge was building AI scoring that felt trustworthy and explainable, not a black box. Resume parsing had to handle varied formats accurately, and the screening logic needed to be customizable per job role without requiring technical configuration. We also had to design a notification and scheduling system that eliminated back-and-forth communication entirely.
Outcome
We delivered a working MVP in six weeks. The platform reduced average time-to-shortlist from four days to under six hours. Hiring managers reported a 70 percent reduction in manual screening effort. The client successfully onboarded eight pilot companies within the first month of launch, which directly supported their seed fundraising conversations. The product was built to scale, with modular components that allowed new features to be added without rearchitecting the core.
Technology
- Next.js
- Python
- OpenAI API
- PostgreSQL
- AWS Lambda
- Supabase
- Vercel
Next.js
Python
OpenAI API
PostgreSQL
AWS Lambda
Supabase
Vercel