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TalentAI - Hackathon Status

Last Updated: February 4, 2026

System Overview

TalentAI is a multi-agent AI system that automates talent acquisition from job description creation to offer generation. Uses Google ADK with Gemini, Supabase, Next.js 14, and FastAPI.

✅ Features Ready for Demo

Feature Status Notes
Sourcing Chatbot ✅ Complete AI-powered candidate search with streaming responses
Pay-per-Reveal ✅ Complete Credit-based candidate contact info reveal system
Video Assessment ✅ Complete Gemini Vision analyzes candidate video responses
JD Creation ✅ Complete Voice/text to structured job description with skills matrix
Resume Screening ✅ Complete AI scoring and ranking of candidates
Offer Generation ✅ Complete HTML offer letter templates
Dashboard ✅ Complete Metrics, pipeline overview, activity feed
Marathon Agent ✅ Complete Autonomous multi-day hiring decisions
Email Service ✅ Complete Assessment invites, offer letters (needs SendGrid key)
Campaigns ✅ Complete Email outreach sequences
Phone Screens ✅ Complete Vapi integration for AI phone interviews

Architecture

Four Core Agents (Sequential Pipeline)

  1. JD Assist - Voice/text → structured job description with skills matrix
  2. Talent Screener - CVs → scored/ranked candidates
  3. Talent Assessor - Generates questions, analyzes video responses via Gemini Vision
  4. Offer Generator - Creates compensation packages and offer letters

Flow

JD Created → Approved → Screening → Shortlist Approved → Assessment → Complete → Offer

Deployment Status

Platform Status URL
Frontend (Vercel) ✅ Deployed https://frontend-95hg0j9mp-bloqai.vercel.app
Backend (Railway) ✅ Deployed talentai-backend on Railway
Database (Supabase) ✅ Active okgawabbcktuvmqqtbzr.supabase.co

Environment Variables Required

Critical (Must Have)

  • GOOGLE_API_KEY - For Gemini AI agents ✅ Configured
  • SUPABASE_URL - Database connection ✅ Configured
  • SUPABASE_SERVICE_KEY - Database auth ✅ Configured

For Full Features

  • SENDGRID_API_KEY - Email notifications
  • VAPI_API_KEY - Phone screening AI
  • APIFY_API_TOKEN - LinkedIn candidate sourcing ✅ Configured

Demo Walkthrough

1. Sourcing Chatbot + Pay-per-Reveal

  • Navigate to /jobs/new
  • Chat: "I need an AI engineer with Python skills, 5 years experience, remote"
  • AI finds and displays anonymized candidates (PII hidden)
  • Click "Reveal Identity & Contact (1 credit)" to see full contact info
  • Credits are deducted and contact info (name, email, LinkedIn) is shown

2. Create Job Description

  • Use classic form or chat interface
  • AI generates structured JD with skills matrix
  • Review and approve

3. Screen Candidates

  • Upload resumes or source from chatbot
  • AI scores and ranks candidates
  • Review shortlist

4. Video Assessment

  • Schedule assessment for candidate
  • Candidate records video responses
  • Gemini Vision analyzes: communication, behavior, content
  • Get recommendation: STRONG_YES, YES, MAYBE, NO

5. Generate Offer

  • Select approved candidate
  • AI generates compensation package
  • Send offer letter via email

🔧 Minor Improvements (Optional)

  1. Campaign send_on_days - Currently sends immediately, not day-specific
  2. JD similar search - Uses mock data (functional but not DB-backed)
  3. Fit score calculation - Placeholder value in sourcing

Tech Stack

  • Frontend: Next.js 14, TypeScript, Tailwind CSS, shadcn/ui
  • Backend: FastAPI, Python 3.11, Google ADK
  • AI: Gemini 2.0 Flash (configurable)
  • Database: Supabase (PostgreSQL)
  • Storage: Supabase Storage (videos, resumes)
  • Email: SendGrid
  • Phone AI: Vapi
  • Sourcing: Apify (LinkedIn scraper)

Completeness: ~85-90%

The system is ready for hackathon demonstration with all core hiring pipeline features functional.