F2 vs. Claude Cowork: Comparing Verticalized Underwriting Platforms to Horizontal AI Models

Should you use a horizontal model like Claude, or invest in a vertical platform purpose-built for your workflow?

Claude is an extraordinary reasoning engine, but intelligence isn't infrastructure. For institutional deal teams that need to spread financials, build models, produce IC-ready memos, and maintain an auditable system of record, the gap between a smart model and a specialized platform is the gap between a tool you use occasionally and a system you build your workflow around.

Executive Summary: F2 vs. Claude Cowork Core Differences

• F2 wins decisively on spreadsheet analysis. F2’s LLMExcel engine scores 95.25% on SpreadsheetBench Verified. Claude’s Python sandbox scores ~43%. That’s the difference between a dedicated spreadsheet engine evaluating real formulas and an LLM writing code to guess at them.
• Claude’s raw reasoning quality is best-in-class. Opus 4.6 features a 1M-token context window. For ad-hoc analysis and general-purpose tasks, it’s a strong option.
• F2 provides the institutional infrastructure Claude lacks. 100+ purpose-built tools, shared workspaces, versioned reports backed by .xlsx databooks, durable 60-minute autonomous workflows, and a precedent deal library.
• Claude is a model; F2 is a platform. F2 uses models (routing across Gemini, GPT, and Claude) with progressive fallback. The value isn’t the routing—it’s the specialized tools those models can use.
• The build-vs.-buy question: Does your firm want to build and maintain the infrastructure around an LLM (Excel engine, workflow orchestration, audit trails), or buy it ready to go?

Spreadsheet Analysis and Native Excel Formula Evaluation

F2 deterministically evaluates live .xlsx formulas using a native, server-side spreadsheet engine to execute complex financial math accurately. Claude Cowork fundamentally lacks this infrastructure, relying instead on error-prone Python sandboxes that attempt to recreate your model's logic from scratch.

F2’s Approach: Dedicated Server-Side Excel Engine

F2’s LLMExcel is a dedicated spreadsheet engine that runs server-side. It is not simply an LLM reading a spreadsheet — it’s specialized infrastructure.
 

• Opens actual .xlsx files with a real spreadsheet engine — the model never sees a text representation of the spreadsheet
• Evaluates real Excel formulas natively — VLOOKUP, INDEX/MATCH, SUMIFS, and circular references all resolve correctly
• 50+ deterministic operations: cell reads, range queries, formula evaluation, pivot aggregation, filtering, matrix lookups, chart creation, batch cell writes, cross-workbook sheet copying
• Edge verification algorithm checks all four boundaries of a spreadsheet before answering, preventing the common failure mode where an LLM truncates a financial model
• Per-workbook write locks for concurrency safety; workbooks stay open in memory across multi-turn workflows
• No client data is used for training — the Excel tools are deterministic. The LLM generates instructions; the spreadsheet engine executes them

Claude’s Approach: The Financial Services Add-In and Code Generation Limits.

In October 2025, they expanded Claude for Financial Services with a native Excel add-in that allows the model to read, analyze, and modify workbooks directly in a sidebar.

While this represents an improvement on basic spreadsheet interaction, it still relies on code generation rather than native formula evaluation — and does not address the audit trail, collaboration, or persistence gaps.

The Bottom Line: F2 evaluates formulas. Claude reasons about them. For a 50-tab financial model with cross-sheet references, F2’s deterministic engine produces correct results every time. Claude relies on auto-generated Python code to reinvent the computation from scratch.

Workflow Architecture: Deal Execution Platforms vs. Standalone AI Models

The distinction between a platform and a model becomes stark across the lifecycle of deal work.

• Data Ingestion: F2 offers persistent, team-wide data rooms where hundreds of documents stay indexed across sessions. For Excel files, the LLMExcel engine queries the live workbook with no chunking boundary problem. Claude is session-bound; each conversation starts fresh unless pinned to a Project.
• Report Generation: F2 creates versioned, editable reports backed by auditable .xlsx databooks with per-cell citations, plus 24+ PPTX editing tools from firm templates. Claude produces polished first drafts in a chat window, but lacks a backing databook or version control.
• Workflow Durability: F2 runs durable workflow orchestration with automatic retry and recovery for up to 60 minutes across dozens of tool calls. Claude executes single-session tasks with no retry/recovery.
• Collaboration and Auditability: F2 provides multi-user shared workspaces and a three-layer audit chain (claim -> formula -> source). Claude is restricted to single-user conversations with non-exportable, conversational citations.

Claude can produce a polished first draft of an IC memo exceptionally fast. The gap appears in everything that happens next: the iterative editing, the audit trail, the multi-person review cycle, and the institutional memory.

Data Integrations: Purpose-Built Financial Tools vs. Generic API Connectors

F2’s integrates with FactSet and PitchBook, each featuring 30+ specialized endpoints with automatic citation tracking, retry logic, and error handling. The data becomes auditable, formula-ready input in a real .xlsx file.

Claude relies on MCP-based connectors, including Aiera, Daloopa, and S&P Global, with LSEG and Moody's also accessible. These connectors require technical setup and configuration, unlike F2's native FactSet and PitchBook integrations.

Where Claude Cowork Excels: Ad-Hoc Research and General Knowledge Work

Here’s what makes Claude a useful tool in your underwriting workflow:

• Frontier reasoning: Opus 4.6 is among the most capable reasoning and coding models in the world.
• 1M-token context window: Ingest and reason over enormous document sets in a single pass.
• Universal applicability: One subscription covers coding, legal review, research, marketing, strategy — any knowledge-work task.
• Ecosystem distribution: 300k+ business customers. Financial data connectors via MCP.
• Claude in Excel and PowerPoint: Sidebar integrations that represent genuine progress from where capabilities were a year ago.
• $20/month entry price: The most accessible frontier AI offering on the market.

For individual analysts, ad-hoc research, and firms with engineering teams willing to build custom workflows, Claude is often the right starting point. But starting point and destination are different things.

F2 vs. Claude Cowork: Feature Comparison Matrix

Which AI Platform Should Your Firm Choose?

The choice between F2 and Claude comes down to whether your firm needs specialized underwriting infrastructure or a generalist AI assistant. Choose F2 to automate complex financial modeling and generate auditable IC memos across a deal team; choose Claude if you need a low-cost, horizontal tool for individual analysts or custom engineering builds.

Who Should Choose F2?

• Private credit funds and commercial banks where the bottleneck is spreading, modeling, and producing auditable IC memos.
• Deal teams of 3+ people who need shared workspaces and versioned reports.
• Organizations that live in Excel and need F2’s LLMExcel engine for complex financial models.
• Teams that need institutional-grade auditability and don't want to build the infrastructure themselves.

Who Should Choose Claude?

• Individual analysts and small teams who need a powerful AI assistant at low cost ($20–$200/month).
• Generalist knowledge workers splitting time across financial analysis, coding, writing, and legal review.
• Firms with engineering teams that want to build custom workflows via API and Claude Code.

Token Economics: Enterprise Infrastructure vs. Capped Subscriptions

Both F2 and Claude use the same Anthropic API at the same per-token rates. The difference is that F2's preprocessing layer eliminates ~98% of token waste.  To put this into perspective, running a complex deal analysis costs around $3,322 in raw Claude API spend, compared to just $62 on F2. This massive reduction in backend costs is exactly what allows F2 to offer unlimited, uncapped usage at a predictable flat seat price.

While Claude appears cheaper on paper, usage caps matter. A single complex IC memo on Claude consumes a massive portion of the rolling 5-hour allowance. To bypass these caps and build a custom tool directly using Claude’s API, an engineering team would need to implement prompt caching, structured extraction, and workflow orchestration. F2 includes this infrastructure out of the box, optimizing token costs (90% reduction on cache hits) natively.

Conclusion: The Build vs. Buy Decision for Institutional Deal Teams

Claude is the strongest general-purpose AI model available today, excellent for ad-hoc research and general tasks. But for private markets underwriting, F2 is the leading infrastructure that no horizontal model currently satisfies.

The question is whether your firm wants to build the infrastructure around a general-purpose model or buy it out-of-the-box and ready to use. For institutional investors, you want a platform that’s read to work for you.

FAQs

Does F2 use Claude as one of its underlying models?

Yes. F2 is LLM-agnostic and routes requests across multiple frontier models, including Claude, Gemini, and GPT. Vision/OCR uses a progressive fallback chain — if one provider fails on a financial table, the system automatically retries with another. F2 leverages Claude’s reasoning while adding its own vertical infrastructure on top.

Can Claude evaluate Excel formulas like F2?

No — not through its standard tools. Claude Cowork’s Python sandbox uses openpyxl, which reads formula strings but cannot evaluate them. The LLM must write equivalent Python logic from scratch for each interaction, and auto-generated code may have bugs (wrong cell references, off-by-one errors, mishandled merged cells). Claude in Excel accesses the formula engine via Excel’s runtime, but only in a local, single-user desktop context. F2’s dedicated server-side engine evaluates formulas natively with 50+ deterministic operations. Same input, same output, every time.

Is Claude’s API model-agnostic?

No. Anthropic’s API only serves Anthropic models (Opus, Sonnet, Haiku). You cannot call GPT or Gemini through it. This is a common misconception. If multi-model access matters, that’s something a firm would need to build separately. F2 routes across multiple providers natively.

Is F2’s multi-model routing just commodity tech?

The routing layer is commodity — F2 is upfront about that. The proprietary value is everything the models can do once they’re called: 100+ tools for financial analysis, a dedicated spreadsheet engine with native formula evaluation, durable workflow orchestration with automatic retry/recovery, and a databook/citation architecture that traces every number back to its source cell. These aren’t RAG pipelines — they’re production infrastructure that took 18+ months to build.

Does F2 train on client data?

No. F2 operates under a strict Zero Data Retention agreement. Your data is never logged, stored, or used to train or fine-tune any AI models by us or our underlying API providers (like Anthropic). Your data is processed in-memory to execute your immediate request and is instantly discarded. F2 is SOC 2 Type II compliant.

Is Claude good enough for institutional underwriting?

Claude excels at reasoning, drafting, and ad-hoc analysis. Where it falls short for institutional underwriting is the infrastructure layer: no persistent team workspaces, no versioned reports with backing databooks, no computational audit trail, no precedent deal library, and no durable workflow orchestration. These aren’t features you can add via prompting — they require product architecture. The question isn’t whether Claude is smart enough. It’s whether your firm wants to build and maintain the infrastructure or buy it out-of-the-box.

Can I use Claude for quick research and F2 for deal execution?

Yes — and many firms do exactly this. Claude for ad-hoc research, coding, and general-purpose tasks. F2 for structured deal diligence, IC memo production, and institutional workflow management. The two are more complementary than competitive.

Ready to see how F2 can accelerate your underwriting workflow? Book a demo today.