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The AI platform built
for fairness.

Audit, detect, and eliminate bias in AI systems across healthcare, justice, finance, and beyond — without writing a single line of code.

Get API Access — Free See how it works

API Tools

158+

Fairness Metrics

Domains

41/41

Validation pass

ISCEV

2022 compliant

Example international organisations we serve:

NHS Trust Ministry of Justice International Labour Organization IMF UNESCO OECD World Bank

How it works

From dataset to audit
in seconds.

No data science degree. No configuration. Upload a CSV, choose your domain, get a certified equity report with plain-language remediation steps.

STEP 01

Upload your dataset

Drop in any CSV — no preprocessing required. The API auto-detects demographic columns, outcome variables, and sensitive attributes.

STEP 02

Select your domain

Choose from 7 FDK domains, BiasClean™ for bias mitigation, or the ERG API for clinical signal analysis. Domain metrics run automatically.

STEP 03

Get your audit report

Traffic-light fairness score, per-metric breakdown, bias sources, and remediation steps — readable by regulators, executives, and legal teams alike.

Our API suite

Three products. Nine APIs.
One mission.

Select a product to explore its capabilities and see a live output preview.

FDK™

Fairness Diagnostic Kit

7 domain APIs · 158 fairness metrics

BiasClean™

BiasClean

v3.0 · Audit-First · 🟢🟡🔴 governance

ERG v2.4

ERG Analysis API

41/41 validated · ISCEV 2022 · FHIR R4

Fairness auditing for every high-stakes domain.

Upload any CSV dataset. The FDK™ runs between 25 and 60 domain-calibrated fairness metrics automatically — detecting disparate impact, group parity violations, and equity gaps with zero configuration.

Auto-detects sensitive attributes in any CSV format

Domain libraries: 25–60 calibrated metrics per sector

Reports readable by regulators, lawyers, and executives

EEOC, ECHR, and EU AI Act alignment built in

Try any FDK domain free

45 metrics

Healthcare

Medical outcomes, patient groups, clinical predictions

36 metrics

Justice

Sentencing, bail, judicial decision algorithms

25 metrics

Hiring & HR

EEOC-aligned recruitment & promotion auditing

31 metrics

Finance

Credit, risk assessment, lending parity

26 metrics

Education

Admissions, placements, resource equity

60 metrics

Business

Promotions, compensation, performance scoring

27 metrics

Governance

Public policy, service delivery, citizen equity

→

Try any API free

For researchers & charities

Audit your AI before it causes harm.

BiasClean v3.0 runs a pre-deployment safety audit before any bias mitigation. The traffic-light governance gives regulators and ethics boards a clear go/no-go signal on any dataset.

Audit-First mode — safety assessment before mitigation

🟢🟡🔴 traffic-light deployment readiness score

Domain-specific weight frameworks per sector

Optional SVM enforcement preserves predictive accuracy

BiasClean™ — Try it free Audit-First safety scoring · traffic-light readiness

BIASCLEAN v3.0 — AUDITSAMPLE DATA

🟢

Deployment Ready

Dataset passed pre-deployment safety audit

Gender

0.92

Ethnicity

0.87

Age group

0.71

Disability

0.84

Postcode

0.52

Clinical AI that earns regulatory trust.

The ERG Analysis API v2.4.0 is the only open-source, ISCEV-compliant electroretinography analysis tool with pre-registered validation and FHIR R4 output. Upload a CSV recording — receive a 4-layer clinical report in seconds.

41/41 Tier 1 validation PASS — independently verified

Baker 2025 normative data (N=407, three age strata)

ISCEV 2022 compliant · LOINC 70943-7 · FHIR R4 output

OSF pre-registered: DOI 10.17605/OSF.IO/6WA42

ERG Analysis API — Try it free ISCEV 2022 compliant · 4-layer clinical report

ERG REPORT · v2.4.0SAMPLE DATA

Signal

🟢

Normal range

B/A Ratio

1.8

Z = +2.1

ISCEV

✓

Compliant

⚠ SAMPLE DATA — Not for clinical use.
Generated from synthetic test data for demonstration only.
ERG Analysis API v2.4.0 · OSF DOI: 10.17605/OSF.IO/6WA42
Baker et al. (2025) normative · N=407 · ISCEV 2022 compliant.
Obtain certified ERG reports from a qualified electrophysiologist.

ERG Analysis API · Clinical AI

The waveform that
sees disease early.

Our ERG Analysis API turns a raw electroretinography CSV recording into a 4-layer clinical decision support report — traffic-light signal quality, Z-scores against Baker 2025 normative data, ISCEV compliance check, and FHIR R4 output.

Detects 6 disease classes: DR, Glaucoma, AMD, RP, Cone Dystrophy, CSNB

Baker 2025 normative reference (N=407, three age strata ≤35 / 36–59 / ≥60)

41/41 Tier 1 validation PASS · OSF pre-registered · LOINC 70943-7

Try ERG API free