Creo is ZenStatement's AI platform purpose-built for modern finance teams, designed to house a growing team of specialized finance agents that execute core finance workflows. The platform addresses the dependency issues finance teams face when critical questions about reconciliation, mismatches, and trends are bottlenecked behind SQL, dashboards, or data teams.
The AI Finance Analyst is the first agent launched under Creo, trained in financial logic and built specifically for finance work. It transforms, reconciles, and analyzes structured financial data, handling financial schemas, edge cases, and controls with accuracy. Unlike BI tools or generic AI layered on spreadsheets, Creo agents are purpose-built for finance workflows and understand reconciliation logic by design.
Users upload a file and ask questions in plain English, receiving structured, audit-ready outputs with full reasoning transparency. The AI Finance Analyst writes and executes Python to find actual answers in transactions, and every insight comes with underlying SQL for verification. This approach provides a new layer beyond visualization tools, focusing on direct data interaction rather than dashboard wrangling.
The platform eliminates the need for SQL knowledge or waiting on data teams, allowing finance professionals to get mismatches flagged, trends visualized, and audit-ready outputs instantly. It enables finance teams to interact with their data more directly while maintaining structured, traceable outputs that meet audit requirements.
Creo targets CFOs, controllers, analysts, and operations leaders who face bottlenecks in financial analysis and reconciliation. The platform represents the beginning of the AI era for the Finance OS and the future of the modern CFO stack, with more specialized finance agents planned beyond the initial AI Finance Analyst.
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Creo is designed for modern finance teams including CFOs, controllers, analysts, and operations leaders who face bottlenecks in financial analysis and reconciliation. The platform specifically targets finance professionals who spend significant time waiting on SQL queries from engineering teams, stitching together CSVs, or dealing with dependency issues when trying to answer critical financial questions. It serves organizations where finance leaders need to question numbers directly rather than relying on data teams or complex dashboard systems.