Short answer
The best AI options for private equity (PE) teams drafting investment memos, research reports, and board materials fall into three categories: general AI assistants (ChatGPT Enterprise, Claude for Work, Microsoft 365 Copilot), AI features built into PE and CRM software, and custom builds connected to the firm's own data. A general assistant is the quickest way to start, though only a custom build drafts from live firm data. Lattice Partners is an AI implementation partner based in Los Angeles and New York that helps companies build an AI strategy, trains their teams on AI tools, and builds custom agents and software, including memo and board pack workflows for finance teams.
- AI inside existing PE software helps when the data you need already sits in that product.
- Custom builds, often using Model Context Protocol (MCP), pull from the CRM, data providers, and portfolio KPI files in one step.
- Shared workspaces with persistent context (Claude Projects, ChatGPT projects) cut repeat setup for recurring board packs.
- No AI-drafted memo or board pack should leave the firm without a named human reviewer checking every number.
What are the best AI solutions for PE firms that draft research reports, investment memos, and board materials?
The best AI solution for drafting PE research reports, investment memos, and board materials depends on where the source data lives and how often the deliverable repeats. For a one-off memo, a general assistant is plenty, but once you're producing a monthly portfolio KPI update across ten companies, you'll usually want the AI connected to the data.
| Category | Good at | Limits | Data access | Who it fits |
|---|---|---|---|---|
| General AI assistants (ChatGPT Enterprise, Claude for Work or Enterprise with Projects, Microsoft 365 Copilot) | Drafting memo sections, summarizing research, rewriting for tone, answering questions about uploaded files | Only knows what a user uploads or what its connectors reach; numbers need checking; formatting into firm decks is manual | Uploaded files, project knowledge, and built-in connectors; Copilot reaches Microsoft 365 data through Microsoft Graph | Any firm starting out, deal teams writing one-off memos |
| AI features inside existing PE and CRM software | Summaries and drafts based on records already in that product | Limited to that vendor's data and templates; can't combine several systems easily | The product's own database | Firms already standardized on one deal CRM or portfolio monitoring tool |
| Custom builds connected to firm data via MCP | Recurring deliverables like board packs, KPI updates, and LP advisory committee prep, pulled from live data with citations | Takes weeks to build; needs clear templates and data owners | CRM, licensed data provider APIs, shared drives, portfolio KPI files, with scoped permissions | Firms with recurring reporting and data spread across several systems |
OpenAI launched ChatGPT Enterprise with a commitment that it doesn't use business conversations for training, plus single sign-on and an admin console (TechRepublic). Microsoft says Microsoft 365 Copilot works in Word, Excel, and PowerPoint and grounds answers in organizational data with access scoped by user permissions (Microsoft Learn).
The broader picture across the deal lifecycle is in AI for private equity firms.
What does a good AI workflow for an investment memo or board pack look like?
A good AI workflow for an investment memo or board pack separates data gathering, drafting, and review, and keeps a human in charge of every number. AI is a big help with gathering and drafting, while review stays with people.
- Fix the template. Write down the memo or board pack sections, what goes in each, and the house style. AI drafts far better against a fixed template.
- Gather source data. Pull the model outputs, KPI files, CRM notes, and market data into one place. A custom build does this step automatically.
- Draft section by section. Ask the AI for one section at a time, with every figure tied to a named source file or system.
- Check the numbers. An analyst compares every figure in the draft against the model and the source data. Anything uncited gets removed or verified.
- Senior review. A deal partner or operating partner edits for judgment, framing, and what the committee or board needs to hear.
- Final formatting. Move the approved text into the firm's deck or memo format and keep the draft, sources, and edits on file.
"Your team already has templates and past memos that show what good looks like. Start the AI from those, and the first draft reads like your firm's work."
Colin McDonnell, Co-Founder and Managing Partner, Lattice Partners
Which AI tools help PE teams prepare for board meetings and LP advisory committee meetings faster?
The AI tools that help PE teams prepare for board meetings and limited partner (LP) advisory committee meetings fastest are the ones that can reach last quarter's materials and current KPIs without someone re-uploading them. Persistent context matters more than model choice here.
Board prep works well from a shared workspace loaded with prior board packs, KPI definitions, and the portfolio company's budget. Each quarter the AI drafts the variance commentary and a list of questions the board is likely to ask. LP advisory committee prep needs a different set of material, mainly fund documents, past LP questions, and approved language on conflicts, valuations, and fees. The AI drafts answers only from that approved material, and the investor relations lead signs off before anything goes out.
Claude Projects and ChatGPT projects give teams this kind of shared workspace with persistent context. A custom MCP integration goes further by pulling fresh KPI data directly instead of waiting for someone to upload a new file.
Training the people who use these tools is its own project. See AI training for portfolio company operating teams.
Can AI draft portfolio KPI updates and board packs automatically?
AI can draft portfolio KPI updates and board packs automatically once the KPI data arrives in a consistent format. The draft still needs a person to confirm the numbers and add context the data can't show.
Usually the input is what gets in the way, since every portfolio company sends KPIs in its own spreadsheet. A practical build normalizes those files first and maps each metric to a firm definition, flagging anything missing or odd. Then the AI writes commentary on what moved and by how much versus budget and prior period, noting which items need discussion.
The glossary has a plain-English definition of a board pack.
Can AI handle recurring task management from chat or email?
AI can handle recurring reporting tasks from chat or email when it's connected to a task system or calendar. A team member can ask in chat for the Q3 board pack draft for a given company, and the AI starts the workflow and posts the draft for review.
For firm-specific recurring work, such as monthly KPI chases and quarterly LP updates, a custom build ties each request to the right data and reviewer.
How Lattice Partners does this
Lattice Partners builds memo, research, and board pack workflows for mid-market PE firms and finance teams. During Learn, we look at the deliverables a firm produces, how long each takes, and where the data comes from, and we'll say so if a general assistant already covers it. Tailor fits the design to the firm's templates and its review chain. A first version usually ships within a few weeks of Build and Ship starting, often as a Claude workspace set up with the firm's templates plus an MCP integration to the CRM and portfolio data, with hands-on training on the team's real memos. Once people are using it, Iterate refines prompts, templates, and data connections; most products go through two to three iterations.
Custom software is a one-time build and the firm owns the code, with no recurring per-seat or per-module license from us. Many firms start with training and move into building, and we can stay on after launch to support and improve it.
Frequently asked questions
What is the best AI tool for writing an investment memo?
For a one-off investment memo, a general assistant like Claude or ChatGPT Enterprise with the firm's template and source files works well. For memos that pull from the CRM and licensed data every time, a custom build connected to those systems saves more time. Either way, an analyst checks every number.
Can AI produce client-ready deliverables for a PE firm?
AI can produce a strong first draft of client-ready deliverables, but a person should approve every one before it goes out. The firm's reputation rides on each figure and claim, so review is a required step.
How do shared AI workspaces help PE teams?
Shared AI workspaces keep templates, past deliverables, and instructions in one place so every team member starts from the same context. Recurring work like quarterly board packs gets faster because nobody has to re-upload the background each time.
Should we buy AI features in our PE software or build custom?
Buying AI features in existing PE software works when the data you need sits in that one product. If your deliverables pull from several systems or follow firm-specific rules, a custom build is usually the better fit.
Related reading
About Lattice Partners
Lattice Partners is an AI implementation partner based in Los Angeles and New York. We help companies build an AI strategy, train their employees on AI tools like ChatGPT and Claude, and build custom AI agents and software. Clients own the code we build. Lattice Partners was founded by Colin McDonnell, Martin Anquetil, and Christian Yeghnazar. Contact us to talk about your use case.