Predictive
& Data Science.

The advanced tier — where most vendors either over-promise a black box or won't touch the governance. inHR ships governed machine learning for turnover and workforce forecasting, plus the data science behind the harder questions: transparent, bias-tested and advisory — built to survive a regulator and a board challenge.

Talk through your use case → All solutions

Handling

SENSITIVE

predictions about people demand transparency, bias-testing and human oversight.

Transparency

GLASS-BOX

every score is explained — the formula is visible, not hidden.

Decision

ADVISORY

human-in-the-loop; predictions never auto-trigger an employment action.

Bias

TESTED

disparate-impact checks across gender, age and other protected traits.

Predictive Turnover

See the leavers before they go — defensibly.

A governed model flags regretted-attrition risk early, with the drivers shown for every score so a manager can actually act. Labelled EXPERIMENTAL until formally assessed, advisory-only, and logged — the way sensitive HR AI is supposed to be run.

SignalRisk + the why

GovernanceGlass-box & logged

UseAdvisory · never automatic

A People Intelligence predictive-turnover view — employees at risk banded low to critical, the risk factors driving the score, risk by department, projected twelve-month exits and an attrition projection, carrying an EXPERIMENTAL badge and an EU AI Act high-risk notice

Live view · flight risk with its drivers visible, labelled experimental and flagged high-risk under the EU AI Act

Data Science & Forecasting

From "what happened" to "what's likely next."

Beyond a single model: workforce forecasting, scenario modelling and driver analysis on your own data — so planning rests on evidence, not a straight-line guess. Every model carries the same governance standard as the turnover engine: transparent, tested and advisory.

ForecastingWorkforce supply & demand

ScenariosModel the "what if"

DriversThe why behind the number

Governed by design

Every predictive and data-science output carries the same guardrail: transparent method, bias-tested, human-in-the-loop, advisory. The science earns trust because it can be explained and defended — not because it's clever.

Glass-boxBias-tested Advisory onlyAudit-logged

The governance is the product

Anyone can score a model. Few can defend one.

Transparent formula engine, bias testing across protected groups, human-in-the-loop by design, data minimisation, EXPERIMENTAL labelling until formal assessment, and an audit trail. Predictions about people are consequential — inHR is built for that from the first line, not retrofitted after a complaint.

Transparent formula engineBias-tested Human-in-the-loopData minimisation Defensible trailAudit-logged

Advanced analytics you can put in front of a regulator.

Bring the prediction or the pay question you're wary of. We'll talk through how to do it defensibly — governance included, not bolted on.

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