People analytics - Available
Illustrative product view. Sample data is fictional and permission labels are educational.
How it works
Each demonstration uses fictional sample data and keeps the source record, actor, permission boundary, and next step visible.
This section explains the concrete operating path in Perelan: the actor, the record, the state change, and the permission boundary stay visible instead of becoming a loose note in chat. Start with a shared definition of the workforce is described through a fictional but product-grounded state so buyers can understand what changes in the workflow and where the limits are.
This section explains the concrete operating path in Perelan: the actor, the record, the state change, and the permission boundary stay visible instead of becoming a loose note in chat. Headcount and composition in context is described through a fictional but product-grounded state so buyers can understand what changes in the workflow and where the limits are.
This section explains the concrete operating path in Perelan: the actor, the record, the state change, and the permission boundary stay visible instead of becoming a loose note in chat. Time-off and schedule patterns where supported is described through a fictional but product-grounded state so buyers can understand what changes in the workflow and where the limits are.
This section explains the concrete operating path in Perelan: the actor, the record, the state change, and the permission boundary stay visible instead of becoming a loose note in chat. Compensation and spend for eligible roles is described through a fictional but product-grounded state so buyers can understand what changes in the workflow and where the limits are.
This section explains the concrete operating path in Perelan: the actor, the record, the state change, and the permission boundary stay visible instead of becoming a loose note in chat. Trend views instead of one-time exports is described through a fictional but product-grounded state so buyers can understand what changes in the workflow and where the limits are.
This section explains the concrete operating path in Perelan: the actor, the record, the state change, and the permission boundary stay visible instead of becoming a loose note in chat. Filters that follow organizational scope is described through a fictional but product-grounded state so buyers can understand what changes in the workflow and where the limits are.
This section explains the concrete operating path in Perelan: the actor, the record, the state change, and the permission boundary stay visible instead of becoming a loose note in chat. Ask the assistant or build a View for a specific question is described through a fictional but product-grounded state so buyers can understand what changes in the workflow and where the limits are.
Product map
These links are curated for the page rather than generated at random.
Questions
Answers are scoped to repository-verified behavior or intentionally point to current customer documentation when policy facts are not public.
Headcount, joiners/leavers, hiring context, compensation/spend, and trend views are represented in the app.
Manager visibility follows their team/reporting scope rather than broad company access.
Analytics reads from the same product records rather than a detached export.
Analytics is a product-defined reporting surface. Views are AI-generated, user-defined dashboards with separate sharing and sandbox rules.
No. The marketing examples are compressed, but the product path still checks the acting user, role, group scope, and domain permission before data is shown or changed.
No. The product demonstrations use fictional names, roles, dates, and values so the workflow is clear without exposing real people or companies.
Next step
Start with the workflow you want to make calmer, then map the people, records, permissions, and handoffs that make it real.