Segmentation with Bias Auditing
Segment your customers and test every segment for disparate impact - targeting lift for marketing, a bias audit report for your DPO.
CUSTOMER BASE - CLUSTER + BIAS AUDIT · LIVE
212,000 customers → 4 segments
Bias audit - protected attributes & proxies
gender balance ······· 4/5th 0.97 ✓
language LT/RU/EN ···· 4/5th 0.91 ✓
⚠ seg C ∝ age 60+ via proxy [app usage] · 0.72 FAIL
mitigation ▸ proxy feature removed → re-cluster
re-audit ····· all segments ≥ 0.85 ✓
How it works
Connect your customer data
Warehouse read-only. Features catalogued; protected attributes and likely proxies flagged before any model runs.
Segment for humans
Interpretable clusters with plain-language profiles, sized and named for marketers - not centroids only a data scientist can read.
Audit every segment
4/5ths-rule disparate-impact tests on gender, age and language, plus proxy detection. Failing features are removed and the model re-clustered.
Ship with an audit report
Every export carries its bias audit report and methodology note. Segments re-audit automatically on every refresh.
Methodology reference
The published method this build is based on, and what it did in production.
Microsoft open-sourced Fairlearn to measure and mitigate group-fairness gaps across protected groups.
Group-fairness auditing · as reported by Fairlearn ↗
Referenced for methodology only. AimRank is not affiliated with, endorsed by, or a customer of these companies; each links to its own public source. Sources last checked September 2026.
The Four Guarantees™ - this build
The scaffold wires all four in. The PoC proves them on your data, as of that day. Only Implementation keeps them true over time: watched, drift-checked, with recourse.
Measured value
~20% campaign conversion lift vs unsegmented sends at reference volume; eval gate: silhouette + stability + full bias pass before ship.
Defensible
4/5ths-rule tests + proxy detection documented per segment; GDPR profiling analysis (Art. 22) and legitimate-interest note included.
Self-improving
Segments re-audited on every data refresh; new features auto-scanned for proxy correlation; drift alerts when segment sizes shift.
Yours & everywhere
Runs inside your warehouse, full source. MCP endpoint - your CRM and campaign tools consume segments directly.
The number, sized honestly
Reference buyer: Lithuanian bank, insurer or telecom marketing team - 50k-500k customers, regular campaign sends, a DPO who has to sign off on profiling.
Three ways to own it
| Tier | What you get | Price | |
|---|---|---|---|
| Scaffolding ★ | The full repo - clustering pipeline, bias-audit harness (4/5ths + proxy scan), audit report generator, MCP server. Reference run on public data. | €1,690 | |
| PoC ★★RECOMMENDED | Clustered and audited on your real customer data - segment quality and the full 4/5ths + proxy audit run end-to-end. Code + bias audit report + quality report yours. No guarantee at PoC. | from€5,000 | |
| Implementation ★★★ | Production: warehouse-native refresh with automatic re-audit, campaign-tool integration, drift alerts, quarterly regulator-ready methodology report - the agreed number (conservative) attaches here. | from €15,000+ from €900/month assurance |
★ = engagement depth. PoC is the recommended path: quality proven on your data before production money. The PoC carries no performance guarantee by design; the agreed number (conservative) attaches at Implementation, informed by the PoC report.
What we don't promise
Ready to see your own number?
Request the build: within 48h you get a personal reply with the value sized to your volume.
No commitment · reply within 48h · your data stays in the EU