We implement Cube as a trusted semantic layer between your warehouse and every downstream consumer. Consistent metrics, enforced business logic, and performant SQL, REST, and GraphQL APIs for BI, embedded analytics, and AI.
We help organizations design Cube as a trusted semantic layer for governed metrics, reusable business logic, and self-service analytics that stay consistent across every consumption layer.
Our Cube implementations are built to serve BI tools, embedded analytics, custom applications, and AI experiences through performant SQL, REST, and GraphQL interfaces.
We integrate Cube with Snowflake, Databricks, BigQuery, Redshift, PostgreSQL, and more, so you gain trusted metrics and flexible access patterns without redesigning your entire data stack.
The semantic layer pays off when definitions are consistent, caching is tuned, and downstream consumers all draw from the same trusted source. That is where we concentrate.
Consistent, reusable data models and metrics that serve as the single source of truth across every team and tool.
REST, GraphQL, and SQL APIs that power BI tools, embedded analytics, and custom applications with sub-second query performance.
Cube embedded directly into your products with proper access controls and tenant isolation for reliable customer-facing analytics.
End-to-end Cube deployment from schema design and connector setup through performance tuning and governance.
A B2B SaaS company implemented Cube as a universal semantic layer to power both internal analytics and customer-facing embedded dashboards, eliminating metric inconsistency across the platform.
Cube acts as a semantic layer between your warehouse and downstream applications, standardizing metrics, enforcing business logic, and serving trusted data to BI tools, embedded analytics, and AI applications.
A semantic layer becomes valuable when teams are seeing conflicting metrics, inconsistent business logic, duplicated reporting work, or a need to reuse trusted definitions across multiple tools and applications.
We design Cube around your warehouse, data model, access requirements, and reporting use cases, then build the semantic layer, APIs, caching strategy, and governance patterns needed for reliable analytics delivery.