See how Cube can help you get the most of your data
Risk, compliance, and trading decisions can't run on numbers no one trusts. Cube is the agentic analytics platform for financial services: analysts and business users ask questions in plain language and get answers grounded in your governed semantic model — the definitions of exposure, P&L, and risk your data team already approved. The same governed definitions serve your BI tools, spreadsheets, and the analytics you embed for clients and partners.
Agentic AI for Financial Services:
AI agents work on top of your semantic model, so every answer uses the metrics your data team governs — not a definition invented on the fly. Analysts explore exposure and P&L without writing SQL from scratch, business users get reports without filing a ticket, and every agent step is explainable for audit and review.
Model access rules once, in the semantic layer, and they hold everywhere the data is consumed — BI, spreadsheets, agents, and embedded analytics. Row-level security and consistent, auditable metric definitions help you meet SOX, GDPR, and internal controls without re-implementing governance in every tool.
Move off the bottlenecks of legacy BI to an AI-native platform that runs on top of your cloud warehouse — Snowflake, BigQuery, Redshift, or Databricks — with no rip-and-replace. Analysts work with governed financial data directly in Excel, always consistent with the model behind it.
Model credit, market, and operational risk once, and every consumer — dashboards, agents, and risk teams — reads the same governed definitions. When an agent surfaces an exposure or a limit breach, the number ties back to the metric your team approved, so you can act on it with confidence.
High-performance caching keeps queries fast even over large, complex datasets, so trading, fraud detection, and market analysis don't wait on the warehouse. Agents and analysts get answers at interactive speed, on data that stays governed.
See how Cube can help you get the most of your data