Hirerify

Smarter hiring through automation

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Hirerify: Smarter Hiring through automation

Inspiration

As a manager in a tech organization, I was constantly working with the human resources team to find the best facilitators and developers for our projects. The process was absolutely hectic—we'd spend weeks sorting through applications, most of which weren't even close to what we needed. Meanwhile, I knew there were talented people out there who just weren't finding us.

The idea hit me during another frustrating hiring cycle where we needed developers for a critical and urgent project but kept getting applications from people with completely different skill sets and we were running out of time. At the end, we had to select the people we found. I realized we could use modern tech to fix this mess. Why not have a platform for recruiters where they can find candidates fit for the job by simply making a post? AI to actually match candidates resumes to the roles we desperately needed? I wanted to build something that would save me and other managers hours of time while giving good candidates a fair shot.

What it does

Hirerify is a two-sided recruitment platform that connects recruiters with candidates through smart matching and streamlined processes. For recruiters, it offers job posting capabilities, AI-powered CV matching with scoring, applicant management with direct messaging, and pro features like interview scheduling and AI-generated interview questions, which are paid features with the use of wallet-based authentication and crypto payment. The platform includes a comprehensive dashboard showing hiring analytics and a settings page for company profile management.

For candidates, Hirerify provides easy registration via email or Google, job browsing with simple CV upload applications, a personal dashboard tracking application status and CV match scores, and an innovative interview system. Where candidates selected for interviews receive a secure one-time access code via email and can record their responses with a re-record functionality, either immediately or within scheduled timeframes set by recruiters.

How we built it

I built everything using bolt.new, which was honestly a game-changer. Instead of writing code from scratch, I could describe what I wanted and iterate quickly. The tricky part was learning to communicate with the AI properly being specific about user flows, data structures, and functionality.

For the recruiter side, I'd prompt something like "Create a dashboard where wallet-authenticated users can post jobs and view applicants with AI matching scores." Then I'd refine it based on what came back. The candidate side was similar I'd describe the job browsing, application process, and interview system step by step.

The AI helped me think through the algorithms too.

Challenges we ran into

The biggest challenge wasn't coding it was learning to prompt effectively. Early on, I'd give vague instructions and get generic results. I had to learn to break down complex features into specific, actionable prompts. Instead of saying "build an interview system," I learned to say "create a component that generates one-time access codes, validates them via email, and handles audio recording with re-record functionality."

The authentication system was tricky because I needed different methods for different users. It took several prompt iterations to explain exactly how wallet auth for recruiters should work differently from email auth for candidates, and how they'd integrate into the same system.

Accomplishments that we're proud of

I'm most proud of creating a platform that actually solves real problems I've experienced firsthand. The AI matching system genuinely helps recruiters find better candidates faster, and the streamlined application process gives job seekers a fair shot without the usual black hole experience.

The interview system turned out better than expected—the re-record functionality and one-time access codes create a professional yet flexible experience that works for both parties. Building all this with generative AI showed me what's possible when you combine domain knowledge with modern tools.

Most importantly, seeing it work in practice when the matching algorithm connects the right person with the right role makes all the prompt engineering and iteration worth it.

What we learned

Building Hirerify with bolt.new was an eye-opening experience. I had never used generative AI for development from start to finish before, but I did it, and it completely changed my mindset on how I work. The biggest thing I learned was prompt engineering; getting the AI to understand exactly what I wanted took practice.

I also learned that even with AI help, you still need to understand what you're building. The AI would generate code, but I had to debug it, modify it, and make sure it solved the real problem. It's like having a super-smart assistant who needs clear instructions.

What's next for Hirerify??

The immediate focus is expanding the AI capabilities with better matching algorithms that learn from successful hires and more sophisticated interview question generation based on job requirements and company culture.

I want to add mobile apps for both recruiters and candidates, since a lot of the hiring process happens on the go. Advanced analytics for recruiters would be huge too, showing hiring patterns, time-to-hire metrics, and candidate pipeline insights.

Long-term, I'm thinking about integrations with popular HR tools. I also want to add a referral system where recruiters can earn free interview credits by referring other companies to the platform. The goal is to keep reducing friction in the hiring process while maintaining the human connection that makes great hires happen.

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