Problem

Private-markets deal teams must make high-stakes decisions from messy, fragmented data rooms containing Excel files, PDFs, and PowerPoints. The core bottleneck is analyst and investment-team time: F2 says customers initially used its tool to overcome the challenge of wading through unstructured data, reporting savings of up to 45 hours per week. The economics are substantial because the work can otherwise require full-time employees costing more than $250,000 annually, while limited team capacity constrains how many deals a firm can screen, diligence, and underwrite.

The killer use case is turning a new deal's raw data room into structured, decision-ready analysis quickly enough to accelerate screening and investment-committee review. F2 is aimed at private credit, private equity, and commercial-bank teams that need to evaluate more opportunities without proportionally increasing headcount, while preserving the institutional knowledge embedded in prior deals.

Product / Service

F2 is an enterprise AI platform and customized deployment of agentic workflows for private-markets investors. It brings together a firm's institutional knowledge, data rooms, and market data; lets teams query that information in one place; surfaces prior diligence findings and investment-committee decisions in natural language; and produces investment-grade analysis, polished memos, and real Excel underwriting files with live formulas, cell references, and dependency tracking. Its workflow spans screening, diligence, underwriting, and portfolio monitoring, with monitoring capabilities covering covenant performance, exposure testing, and fund-level reporting.

The platform uses a multi-model agentic system and proprietary Microsoft Office-native tools to handle large, complex financial workflows, rather than acting as a generic chatbot. F2 claims that customers evaluate deals more than 60% faster and achieve roughly five times the throughput across screening, underwriting, and monitoring. It is designed for regulated institutional users, with SOC 2 certification, GDPR compliance, role-based access, zero data retention, and no training of models on client data.

Market

F2 competes in vertical AI and workflow automation for private-markets investing, particularly private-credit underwriting and diligence, with adjacent applicability to private equity and commercial banking. Its differentiation is domain-specific financial analysis of messy data rooms, complex Excel logic, source traceability, and IC-ready outputs. In its own technical comparison, F2 names Rogo, Hebbia, and BlueFlame as adjacent competitors, positioning them around deal-document extraction, spreadsheet assistance, data-room processing, or investment outreach rather than the full buy-side underwriting workflow.

The company has clear commercial traction rather than being merely pre-product: F2 reports more than 100 private-credit funds and commercial banks as customers, more than $400 billion in assets managed by those customers, over 15,000 deals analyzed, and monthly active users up 650% in 2026. It also reports roughly five-times customer throughput and announced $24 million in total equity funding, including a $14 million seed round in June 2026. The available evidence establishes customer adoption and funding, but does not disclose revenue figures.