Ellis is an AI-native operations platform specifically designed for private credit managers. It addresses the common challenge of fragmented data across various systems by creating a unified, reconciled, and source-verifiable 'book of record'. This platform integrates with a firm's existing infrastructure, including fund administration, general ledger, loan systems, bank feeds, and portfolio tools, without requiring a complete system overhaul. By connecting these disparate data sources, Ellis establishes a governed data layer that ensures consistency and accuracy across all financial operations.
The core functionality of Ellis revolves around its purpose-built AI agents. These agents automate time-consuming and complex tasks that typically consume weeks each quarter, such as reconciliation, financial close processes, reporting, cash forecasting, and portfolio monitoring. For instance, the agents can identify reconciliation breaks, propose fixes for review, and draft various reports like schedules of investments, allowing human teams to focus on analysis and strategic decision-making rather than manual data compilation and error correction. Every action taken by an agent is logged, and every number can be traced back to its original source, providing complete transparency and auditability.
Ellis is built to provide real-time, trustworthy data, enabling private credit managers to always know the precise standing of every fund. It allows users to query the structured book and receive answers backed by clear evidence, showing what changed and its impact. The platform is designed to enhance operational efficiency, reduce manual errors, and provide a single source of truth for all financial data. Notable customers and testimonials highlight its ability to provide real-time data, eliminate reliance on stitched-together spreadsheets, and keep reporting reconciled and current, freeing up teams for higher-value analysis.