--- title: "Best AI Tools for Private Equity, and Who Rolls Them Out | By The People Tech" description: "The AI tools private equity firms buy, by layer, from each vendor's own pages, and when a New York PE firm needs outside help to get its people using them." url: https://bythepeople.tech/insights/best-ai-tools-private-equity --- [Blog](/insights) Best AI tools for PE Best AI tools for private equity firms # The best AI tool for a private equity firm is the one your people _use_ well. The best AI tools for private equity firms come in four layers: a general model the whole firm licenses (Claude, ChatGPT or Microsoft Copilot), document platforms for CIMs and data rooms such as Hebbia and Blueflame AI, sourcing data such as Grata, and an AI-equipped CRM such as Affinity or Intapp DealCloud. Specialist vendors run their own onboarding. A consultant earns a fee when licences are bought and only a few people use them well. By [Tim Miner](/about-us/tim-miner), founder and CEO · Published 22 October 2026 Search results for the best AI tools for private equity are mostly lists, and many are written by the vendors on them. They are useful for a shortlist. The harder question comes after purchase: whether the associates, the IR team and the finance staff who were given the tools now use them on live work. Each vendor on this page is described only from its own pages. The tools ## What are the _best_ AI tools for private equity firms? Start from the document that takes your deal team longest to read, then find the layer that reads it. Private equity firms usually buy AI in four layers, and most end up with more than one. The general model is the one everyone opens. The others are built for one part of the deal cycle, and each vendor sets out its own scope. ### A general model for the whole firm Claude, ChatGPT, Microsoft Copilot or Gemini, licensed firm-wide. It drafts, summarises and answers on whatever document a person gives it. Some specialist tools plug into it: Affinity's MCP server connects its CRM to all four. ### Document platforms for CIMs and data rooms Hebbia describes CIM screening, a first pass over a virtual data room, IC memo prep and expert call synthesis, with outputs citation-linked to source pages. Blueflame AI, Datasite's M&A agent within Grata Intelligence, covers sourcing, diligence, IC memos and portfolio monitoring. ### Market data for sourcing Grata is a private company search platform for sourcing, market mapping and early diligence, with 22M+ company profiles by its own count. It connects with DealCloud, Salesforce and HubSpot. ### A CRM with AI inside Affinity calls itself the AI-first private capital CRM and has launched Ascend, an agent platform. Intapp DealCloud adds AI data capture and a relationship intelligence feed, and says it serves more than 2,400 clients. Choosing ## How should a private equity firm _choose_ between AI tools? Ask which desk loses the most hours to reading, and what a partner would need to see before signing off on the output. Choose by workflow, then test on your own files. Run the shortlist on a CIM your team has already screened, or a data room it has already worked, where you know the answers. A confident wrong answer on a familiar document tells you more than a demo. Read vendor rankings as a shortlist. Blueflame's own 2026 guide answers the best-tools question by describing Blueflame AI. Then check the controls. Ask whether every output links back to the page or cell it came from, whether access follows the permissions you already set and is logged, and whether your data trains anyone's model. Blueflame says client data is not used to train AI models; Affinity says customer data is not used to train models shared across firms. Get the answer in writing, as Affinity's own FAQ advises. The rollout ## Do we need a _consultant_ to roll out AI tools in private equity? Separate installing a product from getting every desk to use it well on live work. For the install, usually not. Specialist vendors bring their own. Blueflame lists dedicated Client Success Representatives for onboarding, rollout, training and custom skill development. Intapp says DealCloud's private equity blueprints, with a preconfigured site structure, reports and workflows, take many firms from signature to production in weeks. Outside help earns its place after that, in the work no single vendor owns: the general model every desk opens, the teams who tried it once and went back, the one-page usage policy compliance will defend, and a monthly number for the COO that is not a licence count. Skills learned on the model itself carry over to whichever product the firm uses next. If your people already use the tools well, you need no consultant. **Vendor onboarding for one platform against an AI adoption retainer across the firm** | | Vendor onboarding | AI Adoption Retainer | | --------------------- | --------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------- | | What it covers | One product: onboarding, rollout, training and set-up of that platform | Every AI tool the firm has licensed, including the general model each desk opens | | Who it reaches | The people given that product | The whole employee base, starting with the teams who tried it once and went back | | What gets configured | Site structure, reports, workflows and custom skills inside the product | Workflow design for the processes where AI earns its place, and only those | | Governance | The product's own controls: permissions, audit trails, no training on client data | The firm's one-page AI usage policy, kept current as the tools change | | Where the skill lives | In workflows built inside that vendor's product | In your people, on the model itself, so it carries to whichever product comes next | Why it stalls ## Why do AI tools go _unused_ after a private equity firm buys them? You have 200 licences and forty people use them. The same forty every month. Buying the tool is the easy part. What decides the return comes after the licence: which work gets handed over, how the request is framed, and how the answer is checked. Most disappointing output is a specification failure. The person did not give the model the firm's process, got a confident wrong answer on a document they knew, and went back to doing it by hand. Licence utilisation misses the figure that matters: how many people use the tools well, on their own work, to a standard a partner would sign. Lunch-and-learns reach the self-starters, who needed help least. What moves the rest is practice on their own material, desk by desk: a deal team on a live CIM, IR on the investor inbox, finance on the quarterly roll forward. Our [guide to AI adoption in private equity](/guides/ai-adoption-private-equity) sets out the order the work goes in. Where we fit ## Where does an AI adoption _retainer_ fit beside the software? Count the people at your firm who use these tools well, by desk, and compare that with the licences you pay for. We sell no tool. By The People works inside the fund on whatever the firm has licensed, and the [AI Adoption Retainer](/retainer) is aimed at one number: how many people in your firm use these tools well. It runs month to month, with no fixed term. Each month it covers four things: prompting practice across the whole employee base, workflow design for the processes where AI earns its place, direct work with the teams who stalled, and a plain account of what changed, written for someone who was not in the room. It also keeps the firm's one-page AI usage policy current as the tools change. Most firms start with a [prompt engineering workshop](/workshops), one team on its own documents. We have delivered over 150 workshops at more than 100 financial services firms. Tell us which tools your people have and the one process that costs the most. If we are the wrong firm for it, we will say so in the reply. ## Questions on AI tools for private equity ### Is ChatGPT or Claude enough for a private equity firm, or do we need a specialist platform? Many firms start with the general model, because every desk can use it on any document. Specialist platforms add deal-specific connections: Hebbia and Blueflame AI read data rooms and link outputs to source pages, and Grata brings private company data. Decide once your people use the general model well, since the gaps are then specific. Our [comparison of Claude and ChatGPT for private equity](/insights/claude-vs-chatgpt-private-equity) covers the first choice. ### Do AI tools for private equity train on our deal data? Ask each vendor and get the answer in writing. On their own pages, Blueflame says a firm's data is not used to train AI models, and Affinity says customer data is not used to train models shared across firms. For the general model, the answer depends on the plan and the data terms your firm signed with that vendor, which is a question for compliance before anything touches a data room. ### Can our CRM connect to Claude or ChatGPT? Some can. Affinity says its MCP server connects the CRM to Claude, ChatGPT, Copilot and Gemini, with updates written back under the same permissions as the CRM. Intapp has announced a DealCloud with Celeste plug-in for ChatGPT for Financial Services. Check which plan includes the connector: Affinity lists its hosted MCP server from the Scale plan up. ### How do we know whether an AI rollout worked? Count how many people use the tools well, by desk, each month, rather than licences. For any process you rebuild, record time and error rate on your own volume, before and after. A partner should be able to check any output against the source it came from. ### What does an AI adoption consultant cost for a private equity firm? We publish no prices. The workshop is priced per session and quoted on the first call, once we know the team and the material. The retainer runs month to month with no fixed term. The fair comparison is a full-time hire, or repeated one-off training that people forget. ## Sources * [Blueflame AI, “Blueflame AI FAQs”](https://blueflame.ai/faqs) * [Blueflame AI, “AI for Private Equity: The 2026 Guide”](https://blueflame.ai/resources/ai-for-private-equity) * [Hebbia, “How Private Equity Teams Use Hebbia”](https://www.hebbia.com/blog/how-private-equity-teams-use-hebbia) * [Affinity, “The same conviction, a new Affinity”, July 27, 2026](https://www.affinity.co/blog/a-new-affinity) * [Affinity, “Affinity AI: Artificial Intelligence for Private Capital”](https://www.affinity.co/product/artificial-intelligence) * [Grata, “Private Equity Deal Sourcing Platform”](https://grata.com/solutions/private-equity) * [Intapp, “How firms improve pipeline management with Intapp DealCloud”](https://www.intapp.com/blog/how-firms-improve-pipeline-management/) ## Read next * [AI Adoption Retainer](/retainer). A month-to-month retainer aimed at how many people in your firm use AI tools well, read by desk each month. * [How to get a private equity firm to actually use AI](/guides/ai-adoption-private-equity). Why licence utilisation is the wrong number and the order the adoption work goes in. * [Claude vs ChatGPT for a private equity firm](/insights/claude-vs-chatgpt-private-equity). The general model choice compared from each vendor's own pages: documents, data controls, admin and Office add-ins. * [AI for private equity firms in New York](/industries/private-equity). Deal screening, CIM review, IC memos and portfolio monitoring, taught and built on your own documents. ## Tell us what you are seeing. If your documents or your experience say otherwise, we would like to hear it. [Book 30 minutes with Tim](https://calendly.com/timminer-1/chat-with-tim) [hello@bythepeople.tech](mailto:hello@bythepeople.tech)