WORKFORCE CONTEXT ENGINE

The pre-built infrastructure behind trusted workforce context

Continuously unifying, modeling, enriching, and governing your workforce data. Every agent, application and workflow gets time-aware, permission-aware context.

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Cleaner data won’t fix a broken foundation.

Your workforce data lives in systems that were never designed to work together. Every HCM migration breaks reporting. Every AI query hits a different system and gets a different answer.

Most organizations try to solve this with a data warehouse and a BI layer. It works until the data changes or two people get different answers to the same question. And every new AI use case means solving the same data and governance problems all over again.

People Data Unification

One unified layer, so AI never works from fragmented context

25+ pre-built connectors unify data across HCM, payroll, ATS, talent, and data warehouses into one governed layer. Reorgs, acquisitions, field changes, system migrations, all handled at ingestion so nothing breaks downstream.

The same person across five systems becomes one record. Timeline-accurate from hire to retire, continuously reconciled as source data changes.

Workforce Semantic Modelling

Shared definitions, so AI answers correctly in context

The same workforce metric can mean different things depending on the context: which populations to include, which organizational structure to use, and which time period to measure. The right answer depends on who's asking and why.

Visier's semantic model resolves this once. 2,000+ metric definitions refined over 16 years, each encoding decisions about criteria, time, and scope. Bi-temporal modeling tracks when it happened and when it was recorded. Retroactive corrections are handled automatically.

Governed Context Delivery

Governed once, so every AI agent inherits the rules

Permissions are evaluated at query time: who's asking, what they can see, which org structure applies, what time period is in scope. The same governance applies to dashboards, Vee, MCP, APIs, and data warehouse connectors.

When you add a new AI agent or delivery channel, governance is already there. No per-channel security build. No separate governance project.