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Building an AI-Powered Interview Platform from Scratch

January 20, 20262 min read

Building an AI-Powered Interview Platform from Scratch

At HyrecruitAI, we set out to solve a problem every growing company faces: conducting consistent, high-quality technical interviews at scale. Here is how we built the technical foundation.

The Problem

Traditional interviews are inconsistent. Different interviewers ask different questions, evaluate differently, and introduce unconscious bias. We wanted to build a platform where every candidate gets a fair, structured interview experience — powered by AI but guided by human expertise.

Architecture Overview

Our platform is built as a monorepo with clear separation of concerns:

  • Frontend: Next.js with React 19, server components for performance
  • Backend: Next.js API routes + dedicated microservices for heavy lifting
  • AI Layer: Custom prompt engineering with structured evaluation rubrics
  • Real-time: WebRTC for video, WebSockets for live transcription
  • Database: PostgreSQL with Drizzle ORM for type-safe queries

The AI Interview Agent

The core of our product is the AI interview agent. It is not a chatbot — it is a structured interviewer that:

  1. Follows a predefined interview plan based on the role
  2. Asks follow-up questions based on candidate responses
  3. Evaluates answers against a rubric in real-time
  4. Generates a detailed report with scoring and recommendations

The key insight was that the AI should augment the interview process, not replace human judgment. Hiring managers still make the final call, but they have much better data to work with.

Real-Time Video Processing

Processing video in real-time is one of our biggest technical challenges. We handle:

  • Live transcription with sub-second latency
  • Speaker diarization to separate interviewer and candidate
  • Sentiment and engagement signals
  • Automatic highlight clipping for review

Lessons Learned

Start simple. Our first version was a glorified video call with a chat sidebar. We shipped it, got feedback, and iterated. The AI features came in v2 after we understood what hiring managers actually needed.

Type safety saves lives. With a team shipping fast, TypeScript and Drizzle ORM catch entire categories of bugs before they reach production.

Monitor everything. When you are processing real-time video with AI, things can fail in creative ways. We invested heavily in observability from day one.

What is Next

We are working on multi-language support, advanced analytics dashboards, and deeper ATS integrations. The goal is to make HyrecruitAI the default way companies conduct technical interviews.