Enterprise use cases are complex by nature. Traditional approaches force teams to oversimplify how they model their business, limiting analytical depth and flexibility.
Complex business use cases get reduced to simpler models, limiting analytical depth
Traditional models capture only part of the use case, compromising the quality of analytics
Limited support for complex hierarchies, relationships, calculations, and business rules
Traditional data models weren’t designed to support modern AI analytics
As data, users, and analytical complexity grow, maintaining performance becomes harder
Model the full complexity of your business use cases, not just a limited view or surface-level metrics
Thousands of dimensions and measures in a single semantic model
Recursive, alternate, unbalanced, ragged, and parent-child hierarchies
Complex relationships, calculations, and business rules
Multiple business domains and analytical perspectives in a single model
Analyze from high-level KPIs to the most granular business detail
Drill from summary to transaction-level detail across 25+ hierarchy levels
Slice and dice across any combination of dimensions and hierarchies
Support complex calculations and comparisons at every level of detail
Migrate existing business logic without rebuilding from scratch
Scale beyond the performance and architectural limits of legacy platforms
Power both BI and AI with the same semantic models, on-prem and in the cloud
Semantic Layer
One-click adaptive modeling to transform your data into ready-to-use semantic models in minutes
Auto-generate models from existing data tables
Connect existing Power BI and Tableau dashboards to Kyvos models in one click
Models optimize continuously as data and query patterns evolve
Build, manage, and evolve semantic models programmatically—with minimal manual effort
Automate the model lifecycle from creation to deployment
Simplify model updates, upgrades, and role management
Access semantic models through APIs without duplicating business logic
Maps KPIs, entities, concepts and knowledge with their rules, weights and causal paths