Codebridge Technology, Inc.
Sep 07, 2026
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AI-Assisted Engineering Recruitment Platform
Completed

AI-Assisted Engineering Recruitment Platform

$50,000+
2-3 months
United States
2-5
view project
Service categories
Service Lines
Artificial Intelligence
Software Development
DevOps
Domain focus
Other

Challenge

Senior engineers spent 200–400 hours/month reviewing test submissions manually. Keyword-based auto-screening let candidates bypass filters. Interview-to-offer ratio of 12% signaled mismatches caught too late.

Senior engineers spent 200–400 hours/month reviewing test submissions manually. Keyword-based auto-screening let candidates bypass filters. Interview-to-offer ratio of 12% signaled mismatches caught too late.

Solution

What We Built:

  • A five-agent system on LangGraph and LangChain.
  • Intent Detection Agent: proprietary 0–100 Relevance Index (career progression, technical fit, open-source contributions, publications)
  • Screening Agent: CV validation with RAG grounded in internal hiring standards
  • Assessment Agent: personalized tests with marker questions to detect AI-generated responses
  • Interview Agent: synthesizes Fireflies.ai transcripts into structured candidate profiles
  • Onboarding Agent: Just-in-Time learning paths from Confluence for new hires

Agents act autonomously only when confidence exceeds 90%. Final rejections require human review. The React Recruiter Dashboard surfaces reasoning chains for transparent override. Hierarchical LLM routing cuts per-candidate cost by 40% to $1.50–$3.00.

Results

  • Full-cycle hiring time: 24 days ? 10–12 days (50% reduction)
  • Candidate response time: ~24 hours ? under 2 minutes
  • Interview-to-offer ratio: 12% ? 38%
  • Engineering test-review time: 200–400 ? 100–150 hours/month
  • Sourcing coverage: 3–5 ? 20+ platforms
  • 24/7 global availability

Tech: Node.js/TypeScript, React, PostgreSQL, GCP, LangChain, LangGraph, LangSmith, LLM-agnostic (Claude, GPT, Gemini).