Interview Intelligence Platform

Part of the worlds-biggest-software-project initiative.

An AI-native platform that transforms unstructured job interviews into evidence-based, auditable hiring decisions through structured interview kits, bias detection, and decision consistency enforcement.

Interview Intelligence Platform helps hiring teams move from gut-feel hiring to structured, data-driven selection. It records and transcribes interviews, tags candidate responses to competency frameworks, detects scoring bias across interviewers, and generates auditable evidence trails for every hiring decision. Built for recruiters, hiring managers, and talent acquisition leaders who need defensible, consistent, and fair interview processes.

Why Interview Intelligence Platform?

Every incumbent is proprietary SaaS with no open-source alternative. BrightHire, HireVue, Metaview, Informed Decisions, and every other player in this space is closed-source. Organisations that need transparency into how AI evaluates candidates -- especially under the EU AI Act and NYC Local Law 144 -- have no option to inspect, audit, or modify the assessment logic.
Enterprise pricing excludes SMBs. Most solutions target large enterprises with complex integration requirements. Small-to-mid-size teams that would benefit from structured interviewing are priced out or forced into tools that require heavy customisation before delivering value.
Bias detection is a black box. Platforms claim to reduce assessment bias by up to 68%, but their detection methods are proprietary. Organisations subject to regulatory bias audits cannot independently verify how bias is measured or mitigated.
No platform closes the quality-of-hire loop. Few incumbents connect interview assessments to post-hire performance outcomes. Without this feedback loop, organisations cannot determine whether their interview process actually predicts job success.
Interviewer coaching is an afterthought. Most platforms focus on post-interview analytics. Real-time guidance that helps interviewers ask better questions, maintain consistent structure, and avoid problematic topics during the interview itself is underdeveloped across the market.

Key Features

Structured Interview Management

Interview kit builder with customisable questions, competency frameworks, and scoring rubrics
AI-powered interview guide generation from job descriptions with competency mapping
Pre-built, validated interview kits for specific industries (fintech, healthcare, tech, manufacturing)
Structured scoring rubrics defining what "good" and "poor" evidence looks like for each competency
Time allocations per interview section to ensure consistent coverage

Recording, Transcription & Evidence Tagging

Consent-managed recording of video, phone, and in-person interviews with high-accuracy transcription
Speaker diarisation identifying who said what throughout the interview
AI-powered competency signal tagging linking specific candidate statements to scored competencies
Automated interview note capture and summary generation in multiple detail levels
Searchable interview archives for retrospective review and cross-candidate comparison

Bias Detection & Fairness

Algorithmic detection of scoring inconsistencies across interviewers and demographic groups
Real-time compliance flagging for potentially discriminatory or off-topic questions
Information limiting across interviews to prevent prior scores influencing subsequent assessments
Fairness dashboard auditing bias patterns by demographic group, role, and hiring manager
Root cause analysis explaining why bias occurred and recommending question rewrites

Interviewer Effectiveness & Coaching

Aggregate analytics on talk-to-listen ratios, question adherence, and scoring calibration
Real-time interviewer coaching during interviews with microcoaching prompts
Individual progress tracking showing interviewer improvement over time
Correlation analysis between interviewer assessments and downstream quality-of-hire

Decision Support & Compliance

Comparative candidate evaluation with side-by-side assessment and ranking
Candidate scorecards with evidence trails documenting selection and rejection rationale
Ideal Candidate Profile learning that improves targeting based on actual hiring outcomes
Full audit logs and compliance documentation for legal defensibility
HRIS integration for quality-of-hire feedback loop connecting assessments to post-hire performance

AI-Native Advantage

Unlike incumbents that bolt AI features onto traditional interview platforms, this project is designed around AI from the ground up. Real-time competency evidence extraction -- trained on IO psychology frameworks -- identifies subtle behavioural indicators that manual note-taking misses. Predictive models recommend which questions best predict job success for each role based on historical outcomes, replacing the current post-hoc effectiveness measurement. A continuously recalibrating quality-of-hire model creates a closed-loop system that demonstrates whether interview assessments actually predict real capability, giving organisations the feedback loop that no incumbent currently delivers.

Tech Stack & Deployment

The platform supports self-hosted, cloud, and hybrid deployment to meet the data residency and sovereignty requirements common in regulated hiring environments. Core integrations include bidirectional ATS connectors (Greenhouse, Lever, Workday Recruiting, iCIMS, SmartRecruiters), video conferencing APIs (Zoom, Google Meet, Microsoft Teams), HRIS systems for post-hire performance tracking, and collaboration tools (Slack, Teams) for workflow integration. Jurisdiction-aware consent management handles the varying recording consent requirements across the EU, US states, and other regions.

Market Context

Companies implementing interview intelligence platforms report 15-30% improvements in quality-of-hire and significant reductions in time-to-hire. The market is led by BrightHire, HireVue, and Metaview, all operating as proprietary SaaS with enterprise-oriented pricing. Primary buyers are talent acquisition leaders, HR directors, and heads of people operations in mid-market and enterprise organisations. Regulatory pressure from the EU AI Act, NYC Local Law 144, and similar legislation is driving demand for transparent, auditable interview assessment tools -- a requirement that closed-source incumbents struggle to address.

Project Status

This project is in the research and specification phase. Contributions, feedback, and domain expertise are welcome.

Contributing

We welcome contributions from developers, domain experts, and potential users. See CONTRIBUTING.md for guidelines.

Important: All contributions must be your own original work or clearly attributed open-source material with a compatible licence. Copyright infringement and licence violations will not be tolerated and will result in immediate removal of the offending contribution. If you are unsure whether a piece of code, text, or other material is safe to contribute, open an issue and ask before submitting.

Licence

Licence to be determined. See discussion for context.