---
title: AI tools for venture capital, and what each sees
description: AI tools VC firms use in 2026 for sourcing, diligence, memos, portfolio monitoring and LP reporting, what each sees of your data, and who each fits.
canonical: https://privatesuperintelligence.si/blog/best-ai-tools-for-venture-capital/
last-updated: 2026-10-15
---

# AI tools for venture capital, and what each sees

The AI tools venture capital firms use in 2026 fall into four groups: general assistants (ChatGPT, Claude, Microsoft Copilot), sourcing and relationship tools (Harmonic, Affinity), document and diligence tools (Hebbia, V7 Go), and portfolio monitoring and LP reporting platforms (Visible, Standard Metrics). The useful question for each is what it does and what it sees of your founder and LP data, so this list describes every tool in its maker's own words, as published on its site on October 15, 2026.

## The short list

| Tool | What it does (from its own site) | What it sees of your data | Fits |
|---|---|---|---|
| ChatGPT Business and Enterprise | General assistant for research, drafting and analysis | What your team pastes, uploads or connects | Firms wanting one assistant for everyone |
| Claude for Financial Services | Due diligence, analysis and IC memos, inside Microsoft 365 apps, with financial data connectors | What you upload or connect, plus licensed data sources | Firms that work in Excel and PowerPoint and buy market data |
| Microsoft Copilot | Assistant over your Microsoft 365 email, files, chats and meetings | Microsoft Graph content each user already has permission to see | Firms already on Microsoft 365 |
| Harmonic | Startup discovery and sourcing | Its own company database, plus your network if you sync inboxes and calendars | Sourcing-heavy funds |
| Affinity | CRM for deal flow with AI agents | Your pipeline, relationships, meetings and email | Firms that run deal flow through a CRM |
| Hebbia | AI document analysis across large file sets | The documents and data you load | Diligence on big data rooms and research |
| V7 Go | AI workflows for deal documents, screening and memos | The documents you process | Repeatable document-heavy workflows |
| Visible | Portfolio monitoring and reporting for investors, fundraising for founders | Portfolio data and founder updates | Funds collecting KPIs from many companies |
| Standard Metrics | Portfolio data collection, analysis, LP reporting and benchmarking | Portfolio data and documents | Funds that want collection handled for them |
| Private SuperIntelligence | AI concierge built for one firm across its own email, documents and data | Your firm's email, documents and data, in a deployment built for your firm alone; the provider keeps no copy | Firms wanting AI across all their information without running it |

## General assistants

**ChatGPT Business and Enterprise (OpenAI).** OpenAI says that "by default, we do not use your business data for training our models," that you own your inputs and outputs where the law allows, and that Enterprise admins control retention, with deleted conversations removed within 30 days unless law requires otherwise. It cites a SOC 2 Type 2 audit and AES-256 encryption at rest. Its strength is breadth: one tool that most of your team already knows. Watch personal accounts, which may train on chats by default. Detail in [ChatGPT for venture capital](/blog/chatgpt-for-venture-capital/).

**Claude for Financial Services (Anthropic).** Anthropic says Claude "processes data, runs complex analyses, and generates models and reports in minutes" and "cites its sources so teams can check the work." It names IC memos and portfolio reviews for asset managers, works in Excel, PowerPoint, Word and Outlook, and connects to data providers including FactSet, S&P Global, Morningstar and PitchBook. On Team and Enterprise plans, Anthropic says it doesn't train on your data by default.

**Microsoft Copilot (Microsoft).** Microsoft says Copilot works across content in Microsoft Graph "that you have permission to access," and that "prompts, responses, and data accessed through Microsoft Graph aren't used to train foundation LLMs." Admins can set retention through Microsoft Purview. One detail for international firms: Microsoft notes that models provided by Anthropic as a subprocessor are currently excluded from the EU Data Boundary. Copilot's reach is only as safe as your SharePoint and Teams permissions, so tidy those first.

## Sourcing and relationships

**Harmonic.** Harmonic calls itself "the startup discovery engine," with "30M+ companies and 190M+ people" in its database, an AI agent called Scout for describing a market and finding companies, alerts on hiring and milestones, and network syncing from inboxes, calendars and LinkedIn. It states ISO 27001 certification and SOC 2 Type II compliance. Its database tracks companies and people from the outside, so the main privacy question is what you sync from your own network.

**Affinity.** Affinity markets AI "embedded in every workflow" and agents that "prep your meetings, capture conversations, and write updates back to your pipeline," and says it handles "high-velocity dealflow" for venture firms. Its security page lists SOC 2 Type II and ISO 27001, and says sensitive data is encrypted at rest and in transit. Because a CRM holds your relationships and email, ask Affinity how its AI features handle model training and which model providers process your data; the security page we read did not cover that.

## Documents and diligence

**Hebbia.** Hebbia says its Matrix product brings "documents and financial data, all in one place" for investors, bankers, lawyers and consultants. Its security page states: "Your documents, prompts, and outputs are never used to train Hebbia's models or any model provider we work with." It lists SOC 2 Type 2, ISO 27001:2022 and ISO/IEC 42001:2023, regional processing in the US and EU, and a dedicated tenant "if needed."

**V7 Go.** V7 says Go turns "complex deal documents into faster investment decisions," with uses including deal screening, investment memos and portfolio reporting for private markets. It states "No training on your data" and "Encrypted end-to-end," along with access controls and audit logs. Good for a firm that repeats the same document workflow across many deals. For how to run one, read [AI due diligence for venture capital](/blog/ai-due-diligence-for-vc/).

## Portfolio monitoring and LP reporting

**Visible.** Visible describes itself as a platform "for investors and founders": investors "centralize portfolio & investment data with AI," automate portfolio reviews and dashboards, and connect AI workflows through MCP, while founders share decks and data rooms and send investor updates. Visible also publishes the AI Sentiment Report, which found 57% of VC firms use AI in internal operations and 16% in LP reporting.

**Standard Metrics.** Standard Metrics offers portfolio data collection "through AI agents and managed services," a data set with metrics traceable to source documents, LP reporting templates and benchmarking against "10,000+ venture-backed startups," plus an MCP server for third-party LLMs. It states: "We are SOC 2 and GDPR certified." For how these fit the quarterly cycle, read [AI for LP reporting](/blog/ai-for-lp-reporting/).

## Where Private SuperIntelligence fits

**Private SuperIntelligence (Mitosis Labs).** An AI concierge for enterprises, family offices and private clients, including venture firms. It works across the firm's own email, documents and data, answers with citations, and acts on the firm's behalf within permissions the firm sets. Each deployment is built for one client, from the hardware to the choice of model provider to where the data is stored, and delivery takes weeks. The provider keeps no copy of the work, trains nothing on it and cannot see the outputs, and a client deployment sends no telemetry back to Mitosis Labs.

It fits a firm that wants the most capable AI across all of its information, set up and run for it. It is not a startup database or a CRM: if you need sourcing data or a pipeline tool, you'd still use one of the tools above. There is no public price list, and the current intake is fully subscribed, so it is not a tool you can sign up for this afternoon. More on [AI for venture capital firms](/venture-capital/).

## How to choose

Visible's survey found tool overload (49%) almost as common a blocker as security concerns (51%). Before adding a tool, ask each vendor:

- Does it train on our data, and does the answer cover the model providers it uses?
- How long does it keep documents, prompts and outputs, and who on its staff can read them?
- Does every figure it produces cite a source document?
- Can it act outside the firm (email, CRM writes, sharing), and can we require approval?
- Can we describe it, function by function, in an LP's DDQ?

## Frequently asked questions

### What are the best AI tools for venture capital?

It depends on the job. Harmonic and Affinity cover sourcing and relationships, Hebbia and V7 Go cover documents and diligence, Visible and Standard Metrics cover portfolio monitoring and LP reporting, and ChatGPT, Claude and Copilot are general assistants.

### Which AI tools for VCs don't train on our data?

On their own sites, OpenAI (business plans), Anthropic (Team and Enterprise), Microsoft Copilot, Hebbia and V7 all state they don't train on customer data by default or at all. Confirm the terms in your contract.

### Do I need a separate AI tool for each part of the fund?

Not necessarily. A general assistant plus one specialist tool covers a lot of the work, and Visible's survey shows tool overload is the second most common barrier to adoption.

### Is Private SuperIntelligence a CRM or a startup database?

No. It works across your firm's own email, documents and data, and you'd keep using a CRM or sourcing database alongside it if you need one.

### How often is this list updated?

The descriptions reflect each vendor's site as accessed on October 15, 2026. Vendors change features and terms often, so check their pages before you buy.


## 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 due diligence for venture capital](/blog/ai-due-diligence-for-vc/)
- [AI for LP reporting and investor relations](/blog/ai-for-lp-reporting/)
- [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

- [Enterprise privacy at OpenAI (OpenAI)](https://openai.com/enterprise-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
- [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
- [Harmonic (Harmonic)](https://harmonic.ai/), accessed 2026-10-15
- [Affinity (Affinity)](https://www.affinity.co/), accessed 2026-10-15
- [Enterprise-grade security (Affinity)](https://www.affinity.co/enterprise-grade-security), accessed 2026-10-15
- [Hebbia (Hebbia)](https://www.hebbia.com/), accessed 2026-10-15
- [Security (Hebbia)](https://www.hebbia.com/security), accessed 2026-10-15
- [V7 Go (V7)](https://www.v7labs.com/go), accessed 2026-10-15
- [Visible (Visible)](https://visible.vc/), accessed 2026-10-15
- [AI Sentiment Report Vol. 1 (Visible, 2026)](https://visible.vc/blog/ai-sentiment-report-v1/), accessed 2026-10-15
- [Standard Metrics (Standard Metrics)](https://standardmetrics.io/), accessed 2026-10-15