Data warehouses and lakes primarily focus on storing and accessing data. CryspIQ focuses on governing and structuring data as a long-term enterprise asset. It establishes consistent business definitions, enables reuse across reporting, analytics and AI, and reduces repeated transformation and reconciliation effort over time.

No. CryspIQ® works with your existing Raw or Staging layers. It leverages the data already stored in platforms like Snowflake or AWS data lakes, avoiding replatforming or disruptive architectural changes. CryspIQ® maps data from source-specific message structures into a standardised enterprise data model. This transforms technical schemas into business-aligned entities such as Customer, Account, Transaction, and Product.

Short answer: most organisations do parts of this — very few do it end-to-end. Many companies already have data warehouses, standard reports, and shared dashboards. But these are often built for specific teams or use cases, resulting in multiple similar models across the business. CryspIQ® is different because it creates one agreed, enterprise-wide data model that everyone reuses. The bottom line: if this was truly in place, teams wouldn’t be reconciling reports, rebuilding the same logic, or debating which number is correct. CryspIQ® turns data into a shared, governed enterprise asset — not a collection of good intentions.

Flexibility is valuable — until metrics stop aligning, reports contradict each other, and confidence in the numbers begins to erode. CryspIQ®’s model is intentionally stable. This ensures everyone works from the same business definitions, changes are controlled and governed, and results remain consistent across the organisation. In practice, this delivers flexibility around a trusted foundation — not chaos.

In practice, it does the opposite. Most delays are caused by rebuilding data logic, resolving inconsistencies, and reconciling numbers across teams. CryspIQ removes this friction by making trusted, governed data immediately reusable — accelerating reporting, decision-making, and AI initiatives.

In most organisations, data standardisation happens per project or per team, which means the same work is repeated again and again. CryspIQ standardises data once, at the enterprise level, and then reuses it across all use cases — including reporting, forecasting, AI and compliance. This is where the real time, cost and efficiency gains are realised.

Many organisations have several “single sources of truth” — often one for finance, one for sales, and another for analytics. CryspIQ® establishes one official version of core business data that is used consistently across finance, operations, customers, assets, analytics and AI. The definitions do not change depending on who is asking, and governance is applied with the same discipline as a chart of accounts. If results still require reconciliation, there is not yet a true single source of truth.

CryspIQ® is a full data platform, comparable to Snowflake and Databricks, designed for enterprises that prioritise consistency, governance, and reuse at scale. All three platforms store and process data at scale. The difference lies in how they are designed to operate. CryspIQ® is built around a single, governed enterprise data model that is native to the platform — not optional or bespoke — ensuring consistent, trusted answers by default. Snowflake and Databricks prioritise flexibility and performance, requiring organisations to design and enforce their own enterprise models. CryspIQ® embeds this discipline directly into the platform.

CryspIQ® is an enterprise data platform designed to give finance leaders consistent, trusted numbers across the organisation. Unlike general-purpose data platforms, CryspIQ® stores and processes data in a single, governed enterprise data model. Financial and operational metrics are defined once, applied consistently, and are auditable by design. This reduces reconciliation effort, lowers data operating costs, and enables faster, more confident decision-making at executive and board level.