Short answer
AI speeds up the recurring reporting cycle at private equity (PE) firms. It puts each company's KPI file into a common format and drafts variance commentary. It also assembles board packs and limited partner (LP) advisory committee materials from approved sources. A person confirms every number before anything goes out. 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.
- The slowest part of the cycle is usually collecting and cleaning KPI files, not writing.
- AI drafts the commentary and the likely board questions, and the deal team edits for judgment.
- Every figure in a draft should trace to a named file, so a reviewer can check it quickly.
What does the recurring PE reporting cycle look like?
Most PE firms run three loops on repeat: monthly KPI collection, a quarterly board pack for each company, and a quarterly LP update. Each loop has a data step, a drafting step, and a review step.
| Loop | Cadence | Where the time goes today | What AI takes on |
|---|---|---|---|
| Portfolio KPI collection | Monthly | Chasing files and reformatting each company's spreadsheet | Reads each file, maps metrics to firm definitions, flags gaps |
| Board pack | Quarterly, per company | Writing variance commentary and building slides | Drafts commentary against budget and prior period, proposes board questions |
| LP advisory committee prep | Quarterly or as scheduled | Finding approved language and past answers | Drafts answers from approved fund material and past LP questions |
| LP update | Quarterly | Pulling numbers across companies into one narrative | Assembles a first draft from the normalized KPI data |
The glossary defines a board pack in plain terms. Tool categories for these deliverables are covered in AI Tools for Drafting Investment Memos, Research Reports, and Board Materials.
How does AI collect and clean portfolio KPIs?
AI collects and cleans portfolio KPIs by reading each company's file and matching every line to a firm-defined metric. It flags anything missing or unusual. Automated cleaning replaces the manual step of copying numbers into a master sheet.
Each portfolio company usually sends KPIs in its own layout, so the work starts with a mapping. A firm writes down its metric definitions, such as recurring revenue or adjusted EBITDA. The tool then maps each company's lines to them. If a line doesn't map, the tool asks a person instead of guessing.
A custom build can also pull files from a shared drive or an inbox on a schedule. MCP for Private Equity Finance Teams explains how Model Context Protocol (MCP) connects AI to systems like these with read-only access to start.
How does AI draft a board pack?
AI drafts a board pack section by section from a fixed template, with each figure tied to a source file. It writes what moved, by how much, and against which comparison, such as budget or the prior period.
A workable draft flow has five steps:
- Load the template. Include the pack sections, the house style, and the last two packs as examples.
- Load the data. Use the normalized KPI file, the budget, and the prior-period figures.
- Draft variance commentary. One section at a time, with the source named next to every number.
- Propose board questions. The tool lists the questions a director is likely to ask, based on the variances.
- Hand off for review. An analyst checks each figure, and the deal partner edits for framing.
Shared workspaces such as Claude Projects keep the template and past packs in one place, so nobody re-uploads background each quarter.
How does AI help with LP advisory committee prep?
AI helps with LP advisory committee prep by drafting answers only from approved material. That includes fund documents, past LP questions, and the firm's approved language. The investor relations lead signs off before anything is sent.
This setup limits what the tool can say. It answers only from a short list of approved sources and cites the one it used. When a question has no approved answer, the tool says so and routes it to a person.
Can AI handle recurring reporting tasks from chat or email?
Yes, when it's connected to the right systems. A team member can ask in chat for the Q3 board pack draft for a company. The tool starts the workflow and posts the draft for review.
For recurring work, a custom build ties each request to the data and the reviewer. The monthly KPI chase can run as a scheduled task that emails each company's finance contact and logs what came back. Anything leaving the firm still needs a person's approval. AI for Private Equity Firms shows where this sits across the deal lifecycle.
What should a PE firm check before trusting an AI-drafted pack?
Check every number against its source, confirm the comparison period, and read the commentary for claims the data doesn't support. The review step is what keeps an AI draft safe to send.
- Numbers. Each figure traces to a named file and cell range.
- Definitions. Metrics use the firm's definitions, not the company's own labels.
- Claims. Commentary describes what happened, and causes are marked as a question for management.
- Approvals. A named person signs off on each pack.
Training analysts to review AI output is a skill of its own, and AI Training for Portfolio Company Operating Teams covers it.
How Lattice Partners does this
Lattice Partners works with mid-market PE firms, finance teams, and the operating teams at their portfolio companies. In Learn, we list each recurring deliverable, how long it takes, and where its data comes from. If a general assistant already covers a deliverable, we say so.
In Tailor and Build and Ship, we set up the template, the metric mapping, and the review chain. When the project is well scoped, the first version usually ships within a few weeks. It's often a Claude workspace loaded with the firm's templates plus an MCP integration to portfolio data. Hands-on training uses the firm's own packs. Most products go through 2 to 3 iterations after launch.
Custom software is a one-time build and the firm owns the code. We don't charge a recurring per-seat or per-module license.
Frequently asked questions
Can AI write a board pack automatically?
AI can write a strong first draft once the KPI data arrives in a consistent format. A person still checks the numbers and adds context the data can't show, such as a management change or a delayed contract.
How do you handle portfolio companies that report in different formats?
Write down the firm's metric definitions, then map each company's file to them. The tool flags lines it can't map and asks a person. After the first quarter, most mappings carry over.
Is it safe to put LP materials into an AI tool?
Use an enterprise version with admin controls and review the vendor's data terms. Limit which confidential documents go into which tool, and keep LP-specific material in a restricted workspace.
Who reviews an AI-drafted LP update?
A named person on the deal team checks every figure, and the investor relations lead approves the final text. Keep the draft, the sources, and the edits on file.
How long does it take to set up AI for recurring PE reporting?
A focused first version, such as a KPI normalizer plus a board pack draft, usually ships in a few weeks. Adoption takes longer, since deal teams have to change how they prepare for each cycle.
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.