Automating and integrating the entire employee lifecycle — from initial application to continuous development — into a single, intelligent ecosystem.
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Set what matters most for this hire. Higher weighs every candidate against this profile and explains every match.
The role title, department, and seniority frame the entire pipeline.
Candidates without these are auto-classified as Category C.
The weighting determines how the final match score is composed. Drag to adjust — the AI explains every decision based on these weights.
Higher narrowed 247 applications down to four people worth your time. One is ready for your decision now.
Sarah completed her assessment last night. She's the strongest match in your pipeline — verified credentials, top-percentile structured reasoning, and clear cultural alignment with the team you described.
Sarah is a senior practitioner with twelve years shipping production ML — most recently leading a four-person team building causal inference systems at a Stockholm fintech. Her hard skills are in the top 2% of all candidates Higher has assessed for similar roles. She communicates with unusual clarity and demonstrates strong leadership through her interview responses.
Anti-distortion checks passed. Social desirability score: low (good).
Every document parsed, cross-referenced against issuing institutions, and analysed for layout and signature anomalies. No black-box judgements — every score has a justification a human can audit.
KTH Royal Institute of Technology · Defended 11 June 2018 · Supervisor: Prof. M. Berg
The AI interviewer adapted its follow-up questions in real time. Every answer was scored against the role's competencies, with direct quotes pulled to justify the rating.
Live-coded against a real production scenario, then a behavioural profile across 184 questions designed to detect inconsistency. Both scored against the role profile, both auditable.
The shaded shape is Sarah. The dashed shape is the target profile defined for this role. Closer to the target on every axis is better.
184 questions · 23 paired inconsistency checks · Identical-meaning items presented far apart in the test.
Every algorithmic decision logged. Every variable used in scoring justified. Every protected characteristic locked at the model level — not as an admin setting. Defensible with regulators, with your union, with your candidates.
Discrimination Act §1 · GDPR Art. 9 special-category data · EU AI Act Art. 10. Every blocked attempt is logged.
Self-service portal. No ticket required. Mean response time tracked publicly.
Voluntary, anonymous self-ID at the end of the candidate journey. Aggregated only — never tied back to individuals.
The union sits in the algorithmic governance committee. Quarterly bias audits are reviewed jointly. This is not consultation theater — they have a vote.
Every AI score the system generated about her, with a plain-language explanation. Every right she has under GDPR, one tap away. A "talk to a human" button that's never more than a swipe from any screen.
Every employee has a 35-minute conversation with the AI each quarter. Higher synthesises their answers and gives every manager a one-page brief — in plain language, before the 1:1.
Maria's first answer was abstract. The AI didn't move on — it pushed for a specific recent moment. That's where the real signal lived.
Calibrated by peer feedback, observed work output, and project review. Not self-rated.
Calibrated to her stated priorities and current skill curve. Not generic e-learning catalog.
Three short open-text prompts every six weeks. Higher clusters the language into themes and never reports on any group smaller than five respondents. The price of anonymity is honesty — and we charge it.
Eight sub-groups had fewer than 5 respondents this quarter. We tell you they exist; we don't tell you what they said. Their data still rolls into the company-wide aggregate.
Maria is ready for a promotion conversation to Staff Engineer. Her quarterly self-reflection, peer feedback, and skills curve all point the same direction. The blocker isn't capability — it's whether she gets the visibility to grow into the role.
4 sub-themes were detected within Engineering but suppressed from this view because each had fewer than 5 respondents. Higher's anonymity threshold is non-configurable. If you need granular breakdowns, the underlying responses cannot be retrieved — by design.
Vertical line marks the 4/5ths (0.80) regulatory threshold. All four ratios cleared with margin. Calculated on representation across application → shortlist → final-stage transitions.
Across all 47 hire decisions in Q1, zero protected characteristics entered any model score. Lock is enforced at the model level, not as a configurable setting. Last verified by external attestation: 14 March 2026 · KPMG Stockholm.