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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.

BlueFlame, now part of the Datasite ecosystem, covers more of the deal lifecycle than almost any AI platform in private markets — sourcing, VDR integration, CRM connectivity, DDQ management. But it doesn't spread your financials. F2's dedicated Excel engine evaluates formulas natively within live .xlsx files and backs every derived number with a three-layer audit trail. If your analysts spend 70%+ of their time in spreadsheets building models and producing IC memos, workflow breadth isn't the bottleneck — analytical depth is.

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.

Rogo is the dominant AI research platform on the sell side — 25,000+ users, seven institutional data partners, and deep coverage of precedent transactions and market intelligence. But it doesn't compute within your existing Excel models. F2's LLMExcel engine opens actual .xlsx files, evaluates live formulas deterministically, and backs every IC memo with a three-layer audit trail from claim to formula to source cell. If your team's bottleneck is spreading a borrower's 40-tab model and producing defensible memos — not generating pitch decks — the architecture difference matters.

Audit Mode embeds auditability directly into deal workflows. Every AI-generated number is written into a live, source-linked Excel Databook so teams can trace, inspect, and export defensible analysis instantly.

In a competitive deal environment, a well-structured screening memo serves as the ultimate gatekeeper of an analyst's time. Explore our 2026 template for private credit memos and learn how agentic AI can automate data extraction with complete source traceability.

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.

Not all AI platforms are equipped to handle the complex math and messy data of buy-side due diligence. Compare the technical architectures of F2, Rogo, Hebbia, and Blue Flame to find the right deterministic reasoning engine for your firm.

Generic LLMs fail at the mathematical rigor required for private market underwriting. This definitive buyer's guide breaks down the transition to deterministic agentic architectures, outlines the five critical pillars for evaluating modern AI platforms, and provides a 90-day roadmap to implement institutional-grade financial analysis.

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.

General-purpose AI treats spreadsheets like flat text, missing the critical formula logic and cross-sheet dependencies required for institutional underwriting. Discover why F2’s deterministic calculation engine and Excel Intelligence layer are the only viable alternatives for error-free financial spreading.

Bridging the manual gap between Excel models and Word documents is the "last mile" of underwriting efficiency. Discover how F2 treats Investment Committee memos as live extensions of your financial spreads, ensuring every narrative, table, and chart stays in sync with your latest data.

Modern underwriting often breaks down due to volume, variability, and complex data. This guide details how "agentic" AI workflows automate financial spreading, structure messy data rooms, and draft IC-ready memos, enabling credit teams to accelerate deal decisions by up to 75% .

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.

Streamline commercial loan underwriting by automating the reconstruction of borrower and guarantor financials. See how AI handles multi-entity ownership chains, analyzes rent rolls and AR aging, and produces audit-ready credit memos for C&I and CRE deals.

Private equity analysts spend hours reviewing data rooms across financial, legal, and commercial documents. Discover how AI due diligence ingests folder hierarchies, extracts customer KPIs, and identifies contract risks—turning unstructured data into investment conviction in minutes.

F2 2.0 marks a major leap forward in financial intelligence for private markets investors. Built on insights from thousands of deals, the latest release introduces advanced Excel Intelligence, full-context analysis, and enterprise-grade collaboration—all designed to help deal teams move from data room to decision with greater speed, accuracy, and conviction.

Explore how F2 2.0 eliminates the trade-off between speed and rigor, delivering true audit-ready AI for the models investors rely on every day.

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.

Arc Intelligence platform achieves 99% accuracy in core complex financial analysis tasks for private credit, according to our internal benchmarking and test data set. In this blog post, we explain our approach to building Arc Intelligence.