---
title: AI due diligence for venture capital
description: Using AI for VC due diligence: reading a data room, drafting the IC memo, checking claims with citations, and keeping the founder's data out of training.
canonical: https://privatesuperintelligence.si/blog/ai-due-diligence-for-vc/
last-updated: 2026-10-15
---

# AI due diligence for venture capital

AI due diligence in venture capital means using a model to read a data room, pull out the numbers, flag gaps and produce a first-draft IC memo that a partner then checks and rewrites. It saves the most time on extraction and first drafts, and it needs two controls to be safe: a citation for every figure, and a tool that keeps the founder's documents out of training. The judgment on the deal stays with the partners.

## What AI does well in VC diligence

Diligence on a Series A or B company usually means a deck, a financial model, a cap table, customer contracts, a few reference calls and a pile of founder updates. Most of the hours go into reading and reconciling. That's where AI helps.

| Diligence task | What AI can do | What a person still does |
|---|---|---|
| Data room triage | List every document, summarize each, flag what's missing from your request list | Decide which gaps matter |
| Metric extraction | Pull ARR, burn, runway, churn and headcount from the model and updates into one table | Check the definitions match across documents |
| Contract review | Find change-of-control, exclusivity and termination clauses across customer agreements | Judge the commercial risk |
| Claim checking | Compare the deck's numbers with the model and the board decks, and list mismatches | Ask the founder about each one |
| Market work | Summarize public research and competitors | Form the thesis |
| Reference call notes | Turn transcripts into themes and quotes | Weigh what people meant |
| IC memo | Draft the memo in your firm's template | Rewrite the recommendation and own it |

Vendors now sell this as a product. V7 says its Go product turns "complex deal documents into faster investment decisions," and lists deal screening and investment memos among its uses. Anthropic says Claude for Financial Services helps asset managers with IC memos and "cites its sources so teams can check the work." Our list of [AI tools for venture capital](/blog/best-ai-tools-for-venture-capital/) compares these and others by what each sees of your data.

## A first-draft IC memo, step by step

An AI investment memo generator is only as good as the inputs you give it and the template you hold it to. A workable sequence:

1. **Give it your template.** Paste your firm's memo headings (team, market, product, traction, financials, risks, terms) and a past memo you liked, with the company details removed.
2. **Load the approved materials.** The deck, the model, the cap table and your call notes. Keep anything the founder marked as restricted out until you've checked the NDA.
3. **Extract before you write.** Ask for a table of every figure with the document and page it came from. Fix the table first.
4. **Draft section by section.** Ask for the market and traction sections from the table, and ask it to mark anything it inferred rather than read.
5. **Write the recommendation yourself.** The draft can list risks and open questions. The view on the deal belongs to the partner who signs the memo.

## Check every figure: citations and errors

The vendors themselves warn that outputs can be wrong. Microsoft's Copilot documentation says AI responses "aren't guaranteed to be 100% factual" and asks users to review output before sending it to others. A memo that misstates a company's ARR to your IC is worse than no memo.

Citations turn that problem into a checking task. If each number in the draft links to the page of the data room it came from, an associate can check the memo figure by figure without starting over. If it doesn't, you end up re-reading the data room anyway. When you test a tool, give it a data room where you already know the answers and count how many figures it cites correctly.

Watch for three common failure modes:

- **Definition drift.** The deck says ARR, the model says annualized revenue, and the two differ. Ask the tool to quote the definition each document uses.
- **Stale figures.** A December update and a March board deck disagree. Ask for the date of each source next to each number.
- **Confident gaps.** The data room has no cohort data, and the draft describes retention anyway. Ask it to say "not in the materials" when it can't find a source.

## Data room risks: training, NDAs and hidden instructions

**Training.** Founder materials should never go into a plan that trains on inputs. OpenAI says personal ChatGPT plans may train on chats unless you turn that off, while Business, Enterprise and Edu don't by default. Read [ChatGPT for venture capital](/blog/chatgpt-for-venture-capital/) for the plan-by-plan detail.

**The NDA.** DarrowEverett, a law firm, wrote in June 2026 that putting deal information into an AI tool may breach an NDA "even if an NDA is silent on AI," because the information goes to a third party's systems under that party's terms. If a founder's NDA restricts disclosure, ask before you use AI on the data room. This is general information, not legal advice.

**Hidden instructions.** OWASP's 2025 Top 10 for LLM applications lists prompt injection first, and notes that "indirect prompt injections occur when an LLM accepts input from external sources, such as websites or files." A data room is a folder of files from someone who wants a yes. If your diligence tool can also send email or update your CRM, limit what it can do without a person approving it.

## AI due diligence checklist

| Before you start | Yes or no |
|---|---|
| The tool's plan does not train on your inputs, in writing | |
| You know how long the provider keeps documents and chats | |
| You've checked the founder's NDA for restrictions on third-party processing | |
| Every figure in the output cites a document and page | |
| The tool says "not found" when a source is missing | |
| Actions that leave the firm (email, CRM writes, sharing) need a person's approval | |
| Each deal's materials stay separate from other portfolio companies' data | |
| You can list the tool by function in your LP DDQ answer | |

That last row matters because LPs ask. ILPA's DDQ 2.0 asks you to list the technology tool used for due diligence of targets, among other functions, and whether a third party performs it. See [How VC firms use AI](/blog/how-vc-firms-use-ai/) for more on what LPs ask.

## Private SuperIntelligence for diligence

Private SuperIntelligence puts the most capable AI behind your diligence, trusted with the whole data room and everything your firm already knows. It works across your firm's own email, documents and data, answers with citations a partner can check, and acts only within permissions you set. Each deployment is built for one firm, and the provider keeps no copy of the work and trains nothing on it. See [AI for venture capital firms](/venture-capital/).

## Frequently asked questions

### Can AI write an investment memo?

AI can write a first draft of an IC memo from the deck, the model, the cap table and your call notes. A partner should check every figure against its source and write the recommendation.

### What are the best AI due diligence tools for VC?

General assistants such as ChatGPT Enterprise and Claude handle reading and drafting, while document tools such as Hebbia and V7 Go focus on large sets of files. Compare them by what each does with your data, as in our [AI tools for venture capital](/blog/best-ai-tools-for-venture-capital/) list.

### Is it safe to upload a data room to AI?

It can be, on a plan that doesn't train on your inputs, with retention you understand, and if the founder's NDA allows it. A personal chatbot account on default settings is the wrong place for a data room.

### How do I stop AI from making up numbers in diligence?

Require a citation to a document and page for every figure, and ask the tool to say when it can't find a source. Test it first on a data room where you already know the answers.

### Can a malicious document in a data room manipulate an AI tool?

Yes. OWASP lists prompt injection as the top risk for LLM applications and includes instructions hidden in files. Keep a person in the loop for any action the tool takes outside the firm.


## Related reading

- [How VC firms use AI, and what stays private](/blog/how-vc-firms-use-ai/)
- [ChatGPT for venture capital: decks, NDAs and LP data](/blog/chatgpt-for-venture-capital/)
- [AI for LP reporting and investor relations](/blog/ai-for-lp-reporting/)
- [AI tools for venture capital, and what each sees](/blog/best-ai-tools-for-venture-capital/)
- [Is ChatGPT safe for confidential information?](/blog/is-chatgpt-safe-for-confidential-information/)
- [What is zero data retention AI?](/blog/zero-data-retention-ai/)
- [What is private superintelligence?](/blog/what-is-private-superintelligence/)

## Sources

- [V7 Go (V7)](https://www.v7labs.com/go), accessed 2026-10-15
- [Claude for Financial Services (Anthropic)](https://claude.com/solutions/financial-services), accessed 2026-10-15
- [Data, Privacy, and Security for Microsoft Copilot (Microsoft Learn)](https://learn.microsoft.com/en-us/copilot/microsoft-365/microsoft-365-copilot-privacy), accessed 2026-10-15
- [Data controls in ChatGPT (OpenAI Help Center)](https://help.openai.com/en/articles/7730893-data-controls-faq), accessed 2026-10-15
- [Loose Lips, Large Language Models: What Your NDA is Missing in the Age of AI (DarrowEverett LLP, June 2, 2026)](https://darroweverett.com/ndas-non-disclosure-agreements-age-ai-practical-steps-analysis/)
- [LLM01:2025 Prompt Injection (OWASP Gen AI Security Project)](https://genai.owasp.org/llmrisk/llm01-prompt-injection/)
- [Due Diligence Questionnaire 2.0 (ILPA, November 2021)](https://ilpa.org/wp-content/uploads/2021/11/ILPA-DDQ-2.0.pdf)