Architecture
How CryspIQ® is put together — how source data reaches the enterprise data model, how quality and security are applied on the way in, how it is consumed, and what a deployment needs on Azure.
Data Model
How CryspIQ® decomposes source records into seven typed fact stores against shared dimensions, how parties relate through dated relationships, how the fact type carries the business-wide definition, and how the link key reassembles a record.
Features
What CryspIQ® does, module by module — sources, mapping, operations, data quality, consumption and security — and which capabilities are included in the Lite, Professional and Enterprise plans.
Lumen AI
Lumen is the AI layer of CryspIQ®. It automates data mapping, answers questions in business language, and never writes SQL — and because every deployment shares one structure, it never has to infer what an unfamiliar warehouse means.
Co-Existence
CryspIQ® works alongside your existing data warehouse, lakehouse or BI stack — no rip-and-replace required. Learn how CryspIQ® integrates with your current data platform investments.
Comparisons
How CryspIQ® relates to data warehousing methodologies, and what a cloud data platform such as Databricks or Snowflake leaves as your responsibility — CryspIQ® runs on top of them rather than replacing them.
Methodology
Learn how the CryspIQ® methodology turns fragmented enterprise data into a governed, reusable data model — reducing duplication, improving trust and accelerating enterprise-wide data efficiency.
Plug-ins
Learn how to build and connect CryspIQ® plug-ins to extend your enterprise data model with custom source integrations and transformation logic.