F2 | AI Platform for Private Market Investors

What

F2 is an AI platform for private markets investors that helps teams move from data room review to investment decision more quickly. It is designed for due diligence and underwriting workflows, with messaging focused on automating financial analysis, surfacing risks, preserving source visibility, and producing investment-committee-ready materials.

The product appears positioned for firms in private credit, private equity, and commercial banking. Its core workflow starts with ingesting deal and firm materials, combining those inputs with institutional knowledge and live market data, then generating analysis, reports, and collaborative outputs that analysts through managing directors can review together.

Features

• Automated financial analysis: F2 calculates core underwriting metrics such as EBITDA, leverage ratios, and interest coverage to reduce manual spreadsheet work in borrower evaluation.
• Context-rich deal evaluation: The platform combines firm precedent knowledge with live market data to help teams validate assumptions and identify risks with more complete context.
• Source-level audit trails: Every output can be traced back to underlying source material, which supports verification and review before decisions are finalized.
• IC-ready report generation: F2 converts prior memos and precedent materials into reusable templates, then produces branded charts, memos, and reports aligned to firm standards.
• Real-time collaboration: Teams can work across roles from analyst to managing director, with edits and comments tracked throughout drafting and approval.
• Private-market-specific analysis modules: The website highlights sponsor and stakeholder analysis, downside risk review, and covenant analysis for underwriting and diligence use cases.

Helpful Tips

• Validate where automation is used most heavily: For evaluation, focus on the parts of diligence where analyst time is spent parsing documents, calculating metrics, and reformatting memos, since that is where F2 is most clearly positioned.
• Review exception handling carefully: F2 states that low-confidence or insufficient-data analyses may be flagged or not completed, so teams should assess how these cases fit their review process.
• Test template quality with real precedent materials: Report generation will likely be most useful when firms provide strong historical memos and clearly defined formatting standards.
• Check governance needs across deal teams: The security and access-control features suggest suitability for enterprise environments, but firms should still map internal approval, retention, and user-permission requirements before rollout.
• Separate confirmed capabilities from broader AI expectations: The site supports claims around analysis, reporting, collaboration, and security, but does not provide detailed evidence for every possible workflow beyond those areas.