Compound is the AI analyst built for buy-side investors. Its analysis scores highest on PE Bench, our private equity benchmark. It gives the whole deal team one shared agent and runs on a live deal the same day.
Rogo is an AI platform for investment banks and other financial firms. Hebbia is built for asking questions across large document sets.
Rogo vs Hebbia vs Compound at a glance
| Compound | Rogo | Hebbia | |
|---|---|---|---|
| Built for | Buy-side investors: private equity, credit, real estate, hedge funds and LP allocators | Investment banks and other financial firms | Investment, banking, legal, and corporate teams |
| How the team works | One persistent agent per deal that the whole team shares; every task builds on the work already done | Many task-specific agents in a shared workspace | Shared deal projects, plus agents that run on their own |
| Full auditability of financial models | Every number in the deck traces through the model to the authoritative source page or cell, one citation click at a time | Answers cite the filing, model or document they came from; numbers in a deck aren’t traced through the model to the source | Models cite a source in each cell; numbers in a deck aren’t traced through the model to the source |
| Works with your firm’s AI stack | Works from the agents your firm already runs, like Claude Code and Codex, through the Compound CLI | Its own app, plus Microsoft Copilot in Excel | Its own app, plus an Excel add-in |
| Getting started | Start on a live deal the same day; see pricing | Demo, then a pilot; pricing on request | Demo, then onboarding; pricing on request |
Why private equity firms choose Compound
- The highest-quality analysis. On PE Bench, our own benchmark of the work a deal team hands a partner, from the quality of earnings to the LBO, IC memo, and deck, on full data rooms, Compound scored 80.5% overall, the highest of every agent tested, including the AI labs’ own agents. Its lead is largest on the messy private rooms, where the seller’s numbers disagree with each other. In one data room, the seller adds back $4.8M of sale costs. Compound rejected $2.9M, spent before the board authorized a strategic review: about $60M of price at the deal’s 21.0x entry multiple. The PE Bench write-up shows each agent’s output side by side.
- One agent for the whole team. The deal team shares one persistent agent and workspace with the deal’s files, tasks and comments, so anyone can pick up the work. A VP comments on a cell and the agent makes the change, and the work keeps running while the team is away. See Collaboration.
- A live deal the same day, at published prices. Sign up and run Compound on a real deal before a procurement cycle. Prices are on the pricing page, and most firms complete security review in under a week.
- Due diligence in your firm’s templates. Compound runs due diligence the way your team does: a quality of earnings review, a rent roll audit for commercial real estate buyers or a fund DDQ, and it fills your firm’s templates for each new deal. On an illustrative industrial park’s rent roll, it found $109.3k a year of base rent that no executed lease supports, about $1.8M of the $48.0M ask. On an illustrative buyout fund’s DDQ, it showed that the fund’s net IRR is 11.8% without its subscription line, against 14.5% as reported.
- A secure enterprise agent. Compound is SOC 2 Type II, encrypts data at rest and in transit, never trains on customer data, and supports SAML and OIDC single sign-on, SCIM, audit logs, and deployment in your own AWS or GCP account. See Security.
FAQ
How does Compound compare with Rogo and Hebbia? Private equity firms also compare research platforms, data terminals, and general AI assistants. Compound is the finance AI platform built for their deal work: its analysis scores highest on PE Bench, and the whole team shares one agent. See ChatGPT and Claude for finance vs Compound.
