Antralio provides an AI-native infrastructure platform that automates data extraction, reconciliation, and reporting for private equity firms. The platform embeds AI agents across a firm and its portfolio companies to convert unstructured documents like leases, rent rolls, and board packs into verified, decision-ready answers with source-level traceability.
Funding
Funding not disclosed
Founders
Product
Problem
Private equity professionals spend up to 80% of their time manually gathering and reconciling data from unstructured documents such as leases, rent rolls, CIMs, capital calls, and board packs. This slows deal execution and portfolio monitoring, delaying decisions and increasing operational risk from human error.
Solution
Antralio embeds AI agents across a private equity firm and its portfolio companies to automate the extraction, reconciliation, and delivery of decision-ready answers. The agents read documents the way a senior analyst would, but at machine speed and scale, and every extracted figure is traced back to its source—a page, clause, or cell—so users can verify outputs instantly. The platform runs across deal pipelines, IC memos, portfolio monitoring, and LP reporting, as well as inside portfolio companies for workflows like lease management and monthly close. By replacing manual document processing with verified, cited answers, Antralio reduces a 200-page rent roll review from two days to three minutes while maintaining field-level accuracy of 98%.
Target Audience
Primary customers are private equity firms, including deal teams, investment operations, and portfolio company finance functions, that need to automate document-heavy workflows across the investment lifecycle.
Features
- AI agents that extract and reconcile data from PDFs, scanned documents, spreadsheets, and handwritten amendments with source-level traceability
- Clickable output rows that link directly to the supporting source document, page, or clause for instant verification
- Field-level accuracy of 98% across thousands of extracted fields, validated by client analysts
- Always-on processing that scales with data volume without requiring additional headcount
- Deployment across both the fund and its portfolio companies, enabling seamless data flow and eliminating PDF-based reporting requests
- Strict data isolation between customers with no use of customer data to train AI models without explicit consent