Your Meeting Prep Agent: Instant Portfolio Insights via WhatsApp, Teams or ChatGPT
Last updated 5 June 2026
The information exists. The problem is reaching it.
Your data room contains everything you need for most meetings you will walk into. The problem is that accessing it takes time you usually do not have: logging in, navigating to the right folder, running a search, opening documents one at a time.
That friction matters most when you are in a car on the way to a meeting with an LP, a JV partner, or a potential acquisition target. The information exists. It is just not accessible in the moment you need it.
Xlagent closes that gap. You ask a question in the tool you already have open. The agent searches your documents and sends the answer back to you.
How Xlagent agents work in the tools you already use
Xlagent integrates directly into the tools your team uses every day: Microsoft Copilot (via a native connector), Microsoft Teams (via a Teams bot), ChatGPT (via a custom integration), Claude (via the Model Context Protocol), WhatsApp, and email.
There is no new interface to learn and no separate application to open. You send a message. The Xlagent agent receives the query, searches across your connected data room and data sources, and returns a specific, grounded answer. The response arrives in the same channel you used to ask.
The agent draws only from your firm's connected documents. It does not generate information it cannot find in your data.
What you can ask
The agent handles questions that would otherwise require opening a data room, running a search, and reading through multiple documents. Some examples:
- "What are the current deal conditions with [JV partner name]?"
- "What is our current net exposure to [tenant name] across the portfolio?"
- "What are the key risks flagged in the [asset name] due diligence?"
- "What obligations do we have under [contract name] before the end of Q3?"
- "Where are we in the acquisition process for [target name]?"
- "What was the last rent review date for the leases at [property]?"
The agent is conversational. You can ask a follow-up question based on the first answer, narrow the scope, or ask for a specific document reference.
When this matters most
| Situation | What you can ask | What the agent draws on |
|---|---|---|
| Before an LP meeting | Portfolio performance summary, key milestones, current exposure | Portfolio reports, financial data, investment memos |
| Before a JV or GP partner call | Current deal conditions, obligations, risk flags | Partnership agreements, deal documents |
| During acquisition evaluation | Key terms, due diligence findings, open items | Data room documents, due diligence reports |
| Before a service provider discussion | Contract terms, renewal dates, obligations | Service agreements, procurement documents |
| Investor relations preparation | Fund-level statistics, asset highlights, reporting status | Fund reports, NAV statements, LP communications |
What the agent draws on
Xlagent connects to your firm's data room documents: contracts, deal memos, financing documents, partnership agreements, due diligence files, and any other documents stored in the connected repository.
For portfolio-level questions, the agent can also draw on structured data: rent rolls, financial models, portfolio company submissions, and utility data where connected. The depth of the answers depends on what is in your connected sources.
Knowledge management is the most common AI use case in finance organisations, at 49% according to Caspian One's 2025 AI in Financial Services Report. The meeting prep use case is the most direct expression of that: getting the right information to the right person at the right moment.
Why generic AI tools do not cover this
Microsoft Copilot, ChatGPT, and Claude can answer general questions. They are not connected to your data room. Asking Copilot about your JV conditions returns a generic answer, not the specific terms in your documents.
Xlagent provides the data layer that connects those tools to your firm's actual information. The same agent that answers your question over WhatsApp also integrates into Copilot and ChatGPT, so the tools you are already paying for start returning answers grounded in your own documents.
The 2025 Gartner AI in Finance Survey found that 58% of finance functions had adopted AI, up from 37% in 2023. Boston Consulting Group's 2024 research found that only 29% of financial institutions report meaningful cost savings from AI. The difference between adoption and results is almost always data access: generic tools without firm-specific grounding produce generic outputs.
Xlagent is designed for that gap. The agent works in the channel you prefer. The answers come from your documents.
For a detailed view of the document workflows Xlagent automates beyond meeting preparation, see Automating document-heavy workflows in private capital.