Document Processing Tool Private Equity in 2026
7 min read
Muhammad AliFounder, consultance.ai
A document processing tool for private equity turns CIMs and data rooms into structured, cited answers and memo drafts. The main 2026 platforms are Hebbia, Rogo and V7 Go, none of which publishes list pricing. The alternative is a custom system built on your own templates, which consultance.ai delivers in about six weeks with the client owning the code.
The shortlist
- PE document processing has to fill your template, cite the source page, and push results into your CRM.
- Hebbia's Matrix returns answers across many long documents in a spreadsheet-style table; pricing is not published.
- Rogo raised a $160 million Series D in April 2026 and its Felix agent covers deal screening, CIM work and data room diligence.
- V7 Go targets private markets workflows and prices on a fixed annual agreement scoped by platform, users and pages processed.
- Test any tool on three past deals: one passed, one closed, one where diligence found a late problem.
A document processing tool for private equity reads the files a deal team lives in, such as CIMs, data room folders, credit agreements and portfolio reports, and turns them into structured answers, tables or memo drafts that link back to the source page. In 2026 the realistic choices are a finance-specific platform such as Hebbia, Rogo or V7 Go, or a custom system built around your own documents, templates and approval steps.
This post covers what each of those three vendors says its product does, based on their own sites and independent coverage fetched on 26 October 2026. It also covers what none of them publish, which matters as much when you are budgeting, and how to decide between a seat license and a build.
What a PE document processing tool has to do
Generic OCR and summarization are not the hard part anymore. The hard part is the shape of PE work. A first-pass screen needs the same twenty fields pulled from every CIM, in the same order, so deals can be compared. A diligence workstream needs every answer tied to a page in the data room, because an investment committee will ask where a number came from.
In practice that means five requirements. The tool has to take in a whole data room, not one PDF at a time. It has to fill your template, not its own. It has to cite the page and the passage behind each answer. It has to respect who is allowed to see which deal. And it has to push results into the systems the team already uses, usually a CRM such as DealCloud or Salesforce and a document store such as SharePoint.
Everything below is measured against those five points. If a requirement is not addressed on a page we fetched, we say so rather than guess.
The main options in 2026
Hebbia
Hebbia describes itself as "AI built for the rigor of finance." Its site lists two products. Matrix is a grid tool for building structured analyses across documents and companies, and Max is pitched as an analyst that works with the whole deal team. The site's solutions menu covers investing, banking, legal and corporate, and the customer logos shown include New Mountain Capital, OHA and 26North.
TechCrunch reported in July 2024 that Matrix can process multiple files of unlimited length and returns answers in a tabular format similar to a spreadsheet. The same article reported a $130 million Series B led by Andreessen Horowitz at a valuation of roughly $700 million, and quoted the CEO saying the product was used by 30% of all asset managers. That figure is the company's own claim, made in 2024.
On integrations, the Hebbia site names SEC filings, earnings transcripts, FactSet, S&P Capital IQ, PitchBook, Preqin, SharePoint, Box, Snowflake and Salesforce. Hebbia does not publish pricing. Its pricing page showed no plans or prices when we fetched it, and the site directs buyers to request a demo.
Rogo
Rogo's site says it executes "end-to-end financial workflows using hundreds of purpose-built financial agents." It states that it is trusted by more than 450 firms in finance, with 60,000 bankers and investors using the product and 200,000 queries a day. Named integrations include OneDrive, SharePoint, DealCloud, Salesforce, FactSet and PitchBook. The site lists SOC 2 Type II, ISO 27001 and ISO 42001 among its security and compliance credentials.
FinTech Global reported in April 2026 that Rogo raised a $160 million Series D led by Kleiner Perkins, bringing total funding above $300 million. That article described an agent called Felix that handles multi-step tasks including deal screening, CIM generation, buyer outreach and data room diligence. At that point the company cited more than 35,000 users at over 250 institutions, with named clients including Rothschild & Co, Jefferies, Lazard, Moelis and Nomura. The higher numbers on the current homepage are more recent figures from the company itself.
One thing to note for a buyout fund: Rogo's named customers and case studies are mostly investment banks and advisors, and its homepage does not use the words private equity. Workflows such as data room diligence and CIM work clearly overlap with a PE deal team, so ask for a PE reference during evaluation. Rogo does not publish list pricing.
V7 Go
V7 Go is the document workflow product from V7, a London company that launched Go in April 2024, according to its Wikipedia entry. V7's site says Go "automates complex, document-heavy workflows across private markets, insurance and real estate." For private markets it names deal screening, due diligence, investment memos and portfolio reporting. It advertises more than 280 starter agents and more than 300 integrations and MCP connections.
V7 publishes customer results, which are self-reported. Its site cites Star Mountain Capital, described as a $5 billion alternative asset firm, reporting 21 times faster processing and 54% fewer errors. A V7 case study describes Moderne Ventures uploading an entire data room and getting back an investment memo in Moderne's own template, with each claim linked to its source document. V7 discloses on that page that Moderne is an investor in V7.
V7 is the only one of the three that explains how it prices. Its pricing page states there is no public price list. Instead it sells a single annual agreement scoped on three factors: platform access, the number of decision-making users, and document volume measured in pages processed. The page says the annual price is fixed and there are no feature tiers.
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| Tool | Positioning on its own site | PE document workflows named | Integrations named | Public pricing |
|---|---|---|---|---|
| Hebbia | AI for finance: investing, banking, legal, corporate | Matrix grid analysis across many long documents; Max for deal teams | FactSet, S&P Capital IQ, PitchBook, Preqin, SharePoint, Box, Snowflake, Salesforce | Not published |
| Rogo | Agent platform for financial institutions, bank-heavy client list | Deal screening, CIM generation, data room diligence (Felix agent) | OneDrive, SharePoint, DealCloud, Salesforce, FactSet, PitchBook | Not published |
| V7 Go | Document workflows for private markets, insurance, real estate | Deal screening, due diligence, investment memos, portfolio reporting | 300+ integrations and MCP connections | No price list; annual fee scoped on platform, users and pages |
None of the three publishes a number, so any budget comparison starts with a demo and a quote. That is normal for enterprise software in this category and is not a mark against any of them.
Where a vendor seat fits
A platform makes sense when your workflow looks like the vendor's default. If the team mostly needs fast answers across filings, transcripts and a data room, and the output is a table or a first draft someone will rewrite anyway, a seat license gets you there quickly. You also inherit the vendor's security certifications and data connectors instead of building them.
The fit gets harder in three places. The first is your template. If your screening memo has a fixed structure, house definitions of adjusted EBITDA, and fields that map one to one into your CRM, check that the tool fills your format rather than its own. V7's Moderne case study shows this is possible on at least one platform, so make it a test, not an assumption.
The second is your judgment rules. A good screen encodes what your fund treats as normal versus a real flag in its sectors, and that lives in the heads of your partners rather than in any product. The third is ownership. With a seat, the prompts, extraction logic and workflow belong to the vendor's platform, and leaving means rebuilding.
The build option
The alternative to buying a seat is building a system for your process. That is what we do at consultance.ai: we build custom finance AI for deal teams, the first system is usually live in about six weeks, and the client owns the code. A typical first build reads inbound CIMs, fills the fund's own screening template with page citations, and writes the result into the CRM. Our AI deal desk systems page describes that pattern, and our page on AI for private equity firms covers the wider set of workflows.
A build is not automatically better. It costs more up front than a pilot seat, and it only pays off if the workflow is stable and high volume. If your team screens a handful of deals a quarter, a vendor tool is likely the cheaper answer.
How to choose
Run any candidate, vendor or build, through the same test before signing. Take three real past deals: one you passed on, one you closed, and one where diligence found a problem late. Load the actual CIMs and data rooms and compare the output against what your team concluded at the time.
- Did it fill your screening template, field for field, without manual reformatting?
- Does every number link to the page it came from, and do the numbers tie?
- Did it surface the issue on the problem deal, and did it raise flags on the other two that your team would have dismissed as normal?
- Can the output go into your CRM without copy and paste?
- What does a year cost at your actual page volume and headcount?
The answers usually make the choice obvious. If you want a structured version of this test, the prompt packs in our free library include diligence checklists, and you can book a call to walk through your own deal flow.
Sources
- Hebbia homepage, fetched 26 October 2026
- Hebbia pricing page, fetched 26 October 2026
- TechCrunch on Hebbia's Series B and Matrix (July 2024), fetched 26 October 2026
- Rogo homepage, fetched 26 October 2026
- FinTech Global on Rogo's Series D (April 2026), fetched 26 October 2026
- V7 Go product page, fetched 26 October 2026
- V7 pricing page, fetched 26 October 2026
- V7 case study: Moderne Ventures, fetched 26 October 2026
- Wikipedia: V7 (company), fetched 26 October 2026
