Crunchr AI operates within the same governance model as the rest of the platform. It inherits the user’s authorization profile, including their roles, organisational permissions, and anonymisation rules. This means Crunchr AI can only access and reason over the same workforce data that the user is authorised to see. It does not receive broader access or bypass existing security controls.

Connecting a general-purpose AI assistant to workforce data still leaves access control, auditing, anonymisation, data isolation, and regional processing up to you. Crunchr AI has these safeguards built in, together with established HR metrics and a people analytics engine that turns business questions into governed analysis.

No. Crunchr uses pre-trained commercial models on an inference-only basis, and customer data is never used to train or fine-tune models. Prompts and aggregated data stay within enterprise cloud environments, governed by contractual security standards and strict retention limits.

Yes, you can verify them. Every insight traces back to calculations, charts, and filters you can inspect, while conversational answers pass a separate AI check against your question and data. Crunchr is EU AI Act-ready by design: AI-generated output is clearly identified, and workforce decisions stay with people.

Crunchr AI shows the metrics and filters behind each finding. For deeper questions, it can use statistics to surface the strongest signals and guide the next investigation. That traceability extends across Crunchr AI: in Story Insights, one click takes you from an insight to its source.

Ask about headcount, hiring, turnover, pay, or movement across the organisation. You can start with the business problem, like why early turnover is rising in a department, without knowing the exact metric or filter. Crunchr maps it to the relevant calculation and cohort using the data available to you.

Yes. Your organisation chooses whether to enable Crunchr AI. Administrators have granular control across AI features: Ask Crunchr can be assigned by user or group, and Story Insights enabled for individual Stories. Existing data permissions still apply, so AI never expands anyone’s access.

Crunchr AI appears where people already work with workforce data. Story Insights sits above a Story page and prioritises findings across its charts; Explainer AI interprets individual charts. Ask Crunchr turns a business problem into a guided analysis. It builds the view, explains what matters, suggests where to look next, and uses each follow-up to take the analysis further.

General enterprise AI could help, but workforce analysis still needs its own governance and calculation layer. Crunchr already provides the metric definitions, row- and field-level access rules, anonymity thresholds, and analytics engine. Those controls and calculations are applied before the model interprets the result.

It removes the work between asking and deciding. A people analytics intelligence layer sits between your question and the data: it knows which metric fits the problem and which shifts deserve attention, then the engine runs the math. You read the brief and start at interpretation.