F2 Blog

Some PE firms have rebuilt underwriting around AI; others are still piloting. The distance between the two groups compounds every quarter rather than holding steady, because adopters get sharper with each deal they run while manual workflows strain as data rooms grow. This article traces where the gap surfaces in deal outcomes and fund economics, why a laggard buying the same platform in two years still doesn't catch up, and what separates leaders from the firms still deciding.

The benchmark wars are over. The price war just started. And the enterprises with the wrong architecture are going to learn that lesson on a budget call.

AI has fundamentally changed how a leveraged buyout model gets built — from financial spreading to debt schedule generation to multi-variable sensitivity testing. This article walks through what changes inside each of the leveraged buyout model's five structural layers, and where the sponsor's judgment and accumulated deal history still carry the deal.

Most private credit firms underwrite every deal as if it were their first — covenant rationale buried in shared drives, pattern recognition walking out the door with every analyst departure. This article explains what a living deal library actually is, the four layers of information it captures, and why the AI platform alone won't deliver an edge without it.

Most private credit firms adopt AI tools and six months later their operating model looks identical. The firms capturing real advantage are doing something different: restructuring the analyst role from assembler to investigator, making sensitivity analysis standard on every deal, and building queryable precedent libraries that compound with every underwriting. Here's what the new operating model actually looks like in practice.

Hebbia is a powerful research tool — it can scan thousands of documents and pull structured data at scale. But it doesn't open your Excel files, evaluate your formulas, or show how a derived number was actually calculated. F2 does. With a dedicated spreadsheet engine that scores 95.25% on SpreadsheetBench Verified and a three-layer audit trail that traces every figure from claim to formula to source cell, F2 is built for the computational work that defines buy-side underwriting — not just the reading.

Claude is arguably the best reasoning model available today — and at $20/month, the most accessible. But intelligence isn't infrastructure. Claude's Python sandbox scores ~43% on SpreadsheetBench Verified; F2's dedicated Excel engine scores 95.25%. For ad-hoc research, Claude is hard to beat. For deal teams that need persistent workspaces, auditable .xlsx databooks, and durable workflows that don't break mid-spread, the gap between a general-purpose model and a vertical underwriting platform is the gap between a starting point and a system of record.

Is your underwriting team stuck with manual data entry or ready for agentic AI? Take our 5-step private market readiness audit to diagnose your workflow bottlenecks and map a 90-day implementation plan.

Unstandardized borrower data room materials are the single biggest barrier to underwriting at scale. Learn how F2 utilizes agentic normalization to act as an intelligent translation layer, converting mismatched PDFs and broken Excel models into structured, investor-ready insights.

Stop moving data from PDFs to Excel and start evaluating credit risk. Learn how agentic AI reasoning eliminates the manual "grunt work" of private market spreading by interpreting complex Excel formulas and normalizing messy borrower financials with institutional-grade precision.

Private credit deals require bespoke financial analysis, involving complex EBITDA adjustments and covenant designs. Learn how AI automates spreading, validates addbacks, and tests covenant structures by interpreting complex Excel formulas and borrower documents with audit-grade precision.

In today’s private credit market, speed wins deals, but only if you know exactly what you’re buying. F2 helps firms eliminate the tradeoff between speed and diligence by combining AI-powered data ingestion, deep financial modeling, and instant benchmarking in one platform. From screening massive data rooms to running scenario analyses and generating IC-ready memos, F2 lets credit teams move first and stay confident in every number. The result: faster term sheets, smarter underwriting, and deal decisions backed by defensible, source-linked analysis. F2 gives modern private credit investors an unfair speed advantage, without compromising rigor.