Engineering hiring
intelligence.
Recruiters operate under extreme time pressure. Application volumes are rising while teams shrink. HireSignal surfaces hiring signals in seconds — not minutes — so you spend your 60 seconds on evaluation, not research.
GitHub signal extraction → project analysis → interview questions → evaluation rubric → hiring documentation. Full workflow. One tool.
<60s
time-to-decision per candidate
$100K+
mis-hire cost avoided
10×
recruiter throughput
100%
human decision — always
The full workflow
From GitHub to hiring documentation
HireSignal covers the entire technical evaluation workflow — not just the first-pass screen.
Candidate GitHub profile
Paste a username. HireSignal fetches repos, commits, README files, code structure, and language data in real time.
Engineering signal extraction
7-dimension scoring: profile, repo quality, community, consistency, technical breadth, social proof, commit quality — with percentile context.
Project intelligence
AI reads README files and repo structure to surface what the candidate actually built — complexity, tech stack, test coverage, CI/CD presence.
Structured interview questions
Role-specific, evidence-first interview questions with scoring rubrics — tailored to the candidate's actual stack and experience level.
Hiring risk assessment
Low / Medium / High risk meter with specific mitigations. You evaluate — the platform provides evidence, never the verdict.
Hiring Evidence Graph
Every signal connects: GitHub data + interview feedback + hiring outcome. The graph learns which signals actually predict success — a data moat that compounds with every evaluation.
ATS export + audit trail
One-click export to Greenhouse or Lever. Full audit log for compliance. Searchable history for every candidate reviewed.
Why HireSignal
Explainable intelligence, not automation.
The strongest compliance framing isn't "not automated" — it's explainable decision support with human oversight.
- Opaque scoring — no explainability
- Make the decision for you (GDPR Art. 22 risk)
- No context on what was actually built
- No interview infrastructure generated
- No human oversight built in
- Legally exposed under EU AI Act & EEOC
An explainable hiring intelligence system designed to assist human evaluators — not replace them.
- Every score explained — full reasoning visible
- Human always makes the final decision
- AI surfaces what they built, not just metrics
- Generates complete interview infrastructure
- Audit log for every evaluation
- GDPR Art. 22 · NYC LL144 · EU AI Act · EEOC
What actually predicts performance
Engineering managers evaluate evidence, not activity.
HireSignal mirrors how technical leaders actually assess engineers — real systems built, not vanity metrics.
Real systems built
What they actually shipped
HireSignal #1 focusCode quality & architecture
Tests, CI, structure signals
Collaboration patterns
PRs, code review, issues
Consistency over time
Long-term contribution trend
Public reputation
Stars, forks, followers
A knowledge graph for engineering talent.
Most HR tools analyze static data once. HireSignal builds a continuously-learning evidence graph that connects GitHub behavior, interview performance, and real hiring outcomes — so signal weighting improves with every evaluation.
The more candidates your team evaluates, the more the system learns which signals actually predict success. Competitors can copy the product. They cannot copy the data.
GitHub signal extraction
Languages, tests, CI, architecture patterns, contribution behavior
Project evidence layer
AI reads each repo: what was built, complexity, stack, production patterns
Interview evidence layer
Live co-pilot session scores connect directly to GitHub evidence
Hiring outcome layer
Advance / Hold / Reject decisions + recruiter notes feed back into signal weighting
The data flywheel
Platform capabilities
Built for the full hiring workflow
From first-pass screening to ATS documentation — every step covered.
Structured Interview Guide
Role-specific, evidence-based interview questions with scoring rubrics — generated per candidate in seconds.
Project Intelligence
AI reads README and repo structure to explain what they built — complexity, stack, tests, CI presence.
Percentile Benchmarking
Every score shows percentile rank and benchmark band. 44/100 finally means something.
Explainable by Design
Every signal has a reason. No black-box output. GDPR Art. 22, NYC LL144, EU AI Act compliant.
Hiring Risk Meter
Low / Medium / High risk with specific mitigations. Language that resonates with HR leadership.
Hiring Evidence Graph
Connects GitHub signals, interview feedback, and hiring outcomes into a knowledge graph. The more you use it, the more predictive it becomes — a compounding data moat.
Batch Screening
Screen up to 20 candidates at once. Compare scores side by side and build shortlists in minutes.
ATS Export + Audit Log
One-click export to Greenhouse / Lever. Full audit trail for every evaluation. Searchable history.
Ready to make it a core hiring workflow?
Enterprise teams get ATS integration, audit trails, evaluation tracking, team collaboration, and compliance documentation — everything needed to move from standalone tool to hiring infrastructure.