Governed analytics platform
Why teams outgrow traditional BI
Different versions of the same metric create conflicting reports, rework, and lower trust in decision-making.
Analytics gets rebuilt per product or scenario, making reuse, OEM delivery, and multi-tenant scaling expensive.
Natural-language analytics is becoming mainstream, but reliability, traceability, and semantic guardrails are often too weak.
Why Datafor
Define metrics, dimensions, relationships, and access rules centrally in the semantic model.
BI, embedded analytics, APIs, and AI run on the same execution path.
RBAC, RLS, OLS, auditing, and lineage across the full lifecycle.
AI runs within semantic and access guardrails, with full traceability.
From semantic model to analytics
Core capabilities
Modeling
Modeling
Calculated fields
Analysis
Cross-filtering
Drill-down
AI analytics
AI chat
Insight generation
Delivery
White-label
SSO-ready
Multi-tenancy
Datafor unifies BI, embedded analytics, and AI on a shared foundation so you can build once, govern centrally, and deliver analytics everywhere.
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