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Agentic analytics for finance and accounting
Finance runs on numbers people can defend. Cube is the agentic analytics platform built on a semantic layer: finance teams ask questions in plain language and get answers grounded in governed definitions of revenue, spend, and margin — the ones you already approved. Analysts stop rebuilding the same reports, and every answer reconciles to the model behind it, whether it lands in a dashboard, a spreadsheet, or Excel.
- Ask questions in plain language and get governed, trustworthy answers
- One semantic model, served to BI, spreadsheets, agents, and embedded analytics
- Runs on top of your cloud warehouse — no rip-and-replace
Agentic AI for Finance & Accounting:
Smarter Data, Faster Finance Decisions
AI agents accelerate reporting and variance analysis on top of governed metrics, so accuracy comes from the model, not manual spreadsheet work. Teams explore trends and validate KPIs directly, in plain language, without waiting on an analyst.
Eliminate Financial Data Inconsistencies
One governed model sits between your ERP, BI dashboards, and spreadsheets, so a number means the same thing in each. Finance teams generate accurate statements and spend less time reconciling and more time explaining.
Enable Real-Time Financial Decision-Making
Finance works with governed data directly in familiar tools like Power BI and Excel, always consistent with the model behind it. Move from reactive to proactive — forecast, adjust pricing, and reallocate with numbers you can act on immediately.
Streamline Compliance and Audits
Consistent, auditable definitions keep financial data aligned with evolving standards, so auditors work from trusted numbers that are instantly available. Audit prep shrinks, and finance spends less time on compliance overhead.
Drive Accurate Financial Planning and Forecasting
FP&A works from one governed analytical model instead of stitching sources together by hand. The result is more accurate forecasts, aligned budgets, and faster strategic adjustments.
Ready to upgrade your data stack?
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