F2 vs. Ellis AI: Comparing deal execution to fund operations

TL;DR: F2 is the agentic operating system for private credit deal teams, taking a deal from data room to investment committee decision and turning that deal history into a compounding asset. Ellis AI is an operations platform that reconciles fund administrator, ledger, and loan accounting data into one book after deals close.

Deal teams evaluating AI for underwriting will find F2 built for their work, while CFOs and COOs evaluating AI for fund operations will find Ellis best suited for theirs.

Executive summary: F2 vs. Ellis AI core differences

F2 is an agentic operating system built for buy-side underwriting. It combines:

• Deal Intelligence, the workspace where analysts create deals and carry out screening, diligence, underwriting, and IC memo drafting, with a dedicated agent on each deal
• A native, server-side Excel engine that deterministically evaluates live workbook formulas, scoring 95.25% on SpreadsheetBench Verified
• Institutional Knowledge, a precedent library built from the firm’s own IC memos, models, CIMs, and CRM data, structured into a taxonomy tailored to the firm’s portfolio

F2 serves private credit funds, commercial banks, and PE deal teams collectively managing $400B+ in assets.

Ellis AI is an operations platform for private credit. Founded by Ryan Williams, who previously founded Cadre, it emerged from stealth in July 2026 with a $10M+ seed led by First Round Capital. It combines:

• Direct connectors to fund administrators, general ledgers, loan accounting systems, and bank feeds
• Continuous reconciliation of positions, covenants, and cash flows across those sources, with every figure traced to a GL account, loan tape row, or source cell
• Four agent categories: reconciliation and exception management, close and reporting, forecasting and scenarios, and portfolio monitoring
• Target buyer: CFOs and COOs of private credit funds managing $100M to $1B in AUM

Where each platform sits in the private credit lifecycle

F2’s approach: from data room ingestion to investment decision

A deal enters F2 when the team creates it in Deal Intelligence and adds the data room files. From there:

• The data room is indexed, and borrower financials are spread into a databook
• Models are built and stress-tested inside a live Excel workbook
• The IC memo is drafted in the firm’s own format, with every figure carrying a citation chain from claim to formula to source file
• The completed deal is stored in Institutional Knowledge, where it becomes precedent data for the next one

Ellis AI’s approach: the fund, after the deals close

Ellis's work begins after a deal has closed and the position is already sitting in the loan accounting system and fund administrator records. Here is how the platform works:

• Data is connected from fund admin, GL, loan accounting, and borrower compliance certificates
• Positions, covenants, and cash flows are reconciled across sources, with breaks flagged for review
• Agents draft close packages, reporting, and forecasts for the finance team to approve

Which data each platform’s workflows are built on

Each platform is built on a different set of inputs, which determines where a number traces back to when an associate or MD fact-checks a report or IC deliverable.

F2’s approach: deal documents, classified the way the firm thinks

F2's workflows are built on the deal's own documents and models: the data room, CIMs, borrower financials, and Excel workbooks.

• Deals are classified at intake in the firm's own taxonomy. Industry, capital structure, vintage, and deal type follow how the firm already categorizes deals, so retrieval and agent work match the firm's vocabulary.
• Traceability points inside the deal file. A figure in the memo traces to the databook formula, the source cell, and the original page in the data room, computed by a deterministic engine rather than approximated by a language model.

Ellis AI's approach: the fund's accounting data, reconciled from systems the firm already uses

Ellis's workflows are built on data other systems have already structured: fund administrator data, the general ledger, loan accounting, bank feeds, and compliance certificates, reconciled into one book without replacing any of them.

• Traceability points across systems. A figure in a report traces to a GL account, a loan tape row, or a source cell in an administrator file, and Ellis flags where sources disagree.
• Excel is replaced. Ellis's customers describe moving off "crash-prone" Excel models and workbooks "stitched together" from multiple sources.

F2 treats Excel as a first-class computational surface for building and auditing the model. Ellis treats spreadsheets as the manual process its reconciled book removes.

Agentic capabilities: F2 vs. Ellis AI

Both platforms deploy agents to absorb labor-intensive work in their domain so team members can focus on judgment-based decisions. F2's agents take on the tedious requirements of underwriting, from spreading through memo drafting, and Ellis's agents handle the operational requirements of the fund's book, from reconciling records across systems through drafting the close.

F2's approach: a dedicated deal agent inside Deal Intelligence

• Every deal in Deal Intelligence gets its own agent, Adam, which holds the full context of that deal and works as a member of the deal team, while a firm-level Agent answers cross-deal questions across Institutional Knowledge
• Adam executes long-horizon autonomous workflows on the deal (spreading, model construction, memo drafting, precedent benchmarking) and lays out its plan, assumptions, and data gaps before it begins
• Every output carries the audit chain in Audit Mode, so the analyst reviews the result and owns the decision
• Agents operate on F2's model-agnostic harness, so swapping the underlying model is a configuration change

Ellis AI's approach: agents across the fund book, handling operational work

• Reconciliation and exception management: matches records across the fund administrator, general ledger, and loan accounting system, surfaces breaks, and proposes fixes for the finance team to accept
• Close and reporting: drafts schedules of investments and reporting packages for review and sign-off
• Forecasting and scenarios: models liquidity and fund outcomes on live portfolio data
• Portfolio monitoring: tracks changes in performance and surfaces alerts

How each platform interacts with the rest of your stack

F2 connects to deal-side systems and replaces scattered deal folders

F2 takes in the deal's data room files, whichever VDR the team uses, and integrates with PitchBook, FactSet, DealCloud, SharePoint, Dropbox, and Outlook. Institutional Knowledge replaces the shared drives where past deal context usually lives and grows with each completed deal, so the firm’s own history becomes the asset.

Ellis AI connects to fund accounting systems without replacing any of them

Ellis sits on top of the fund admin, GL, and loan accounting stack without replacing them, deployed as a private tenant by default with engineer-led onboarding alongside the finance and operations team.

Where each platform is the stronger fit

Where F2 is the stronger fit

• Underwriting and diligence. Spreading financials, building LBO models, working sensitivity cases, and drafting IC memos in the firm’s format
• Committee-grade auditability on the deal. Every figure traceable from memo to formula to source page
• Institutional memory for deal decisions. Benchmarking new deals against the firm’s own precedents, with the library growing on each deal
• Enterprise security posture. SOC 2 Type I and Type II certified, GDPR compliant, zero data retention, and no training on client data

F2 is the better fit for deal teams whose core workflow is underwriting deals.

Where Ellis AI is the stronger fit

• Reconciled book of record. Continuous reconciliation across fund admin, GL, and loan accounting
• Close and reporting. Agent-drafted schedules and reporting packages, with the finance team signing off
• Post-close visibility. Portfolio monitoring, forecasting, and scenario analysis on live fund data
• Private-tenant deployment with engineer-led onboarding for the CFO office

Ellis is the better fit for CFO and COO teams that need fund data to agree across every source system before they close and report.

F2 vs. Ellis AI: feature comparison matrix

Conclusion: deal underwriting or fund operations

Ellis AI reconciles fund administrator, ledger, and loan accounting data into one book so private credit finance teams can close and report on numbers they trust.

F2 is the agentic operating system for the underwriting process itself: Deal Intelligence to underwrite the deal, a deterministic Excel engine and audit chain to prove every figure, and Institutional Knowledge to make each completed deal precedent for the next. For private credit deal teams evaluating AI, F2 is the platform that best fits the required tasks.

Frequently asked questions: F2 vs. Ellis AI

Is Ellis AI a direct competitor to F2?

No. F2 is deal-execution infrastructure for underwriting teams; Ellis is an operations platform for private credit CFO offices. They serve the same firms at different points in the deal lifecycle.

Can a private credit firm use both F2 and Ellis AI?

Yes. F2 takes the deal from data room to committee decision, and Ellis reconciles the fund’s book once positions exist in loan accounting and fund admin.

Does Ellis AI do underwriting or IC memos?

Its public materials describe reconciliation, close, reporting, forecasting, and portfolio monitoring for the finance team. They do not describe screening, diligence, underwriting, or IC memo drafting.

Which platform has better source traceability?

F2 can trace a memo figure to the databook formula, source cell, and original data room page. Ellis traces a book figure to a GL account, loan tape row, or administrator file, and flags breaks between systems. For an investment committee reviewing an IC memo, F2’s chain is the most relevant one.

Which platform is more mature?

F2 serves private credit funds, commercial banks, and PE teams managing $400B+ in assets and is SOC 2 Type I and Type II certified. Ellis emerged from stealth in July 2026 with a $10M+ seed, built alongside private credit managers managing $50B+ in AUM.

Does F2 train on client data?

No. F2 operates under zero data retention and never trains on client data.

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