Go from raw financial data to deployed models and reports with an AI agent that handles discovery, analysis, and deployment in one platform.

Zerve is built for the complete financial analysis workflow, not just one piece of it. It starts by automatically mapping your data warehouse with its Data Discovery feature, giving your analysis immediate context without manual schema review. From there, you work in Agentic Notebooks where an AI partner helps you write, run, and fix Python code for tasks like churn analysis, revenue forecasting, or market segmentation. This is a significant step up from generic AI chats that only provide code snippets. For business analysts, Zerve turns these notebooks into interactive, Conversational Reports that stakeholders can query themselves, closing the loop between analysis and business action. Crucially for finance, the platform is built with enterprise security in mind, offering on-premise, private cloud (VPC), and even air-gapped deployment options to keep sensitive data secure. A key proof point is its ability to handle massive datasets; one team processed a 4.3 billion-row dataset by running 24 processes in parallel, a task that previously crashed high-end notebooks.