# LP reporting: use requests to improve next quarter's definitions, not to rank investors Canonical: https://opendataroom.com/guides/lp-reporting-questions-from-ledger Updated: 2026-10-17 Explain the changed definitions between two quarterly LP reports. Keep the relevant documents in OpenDataRoom, then let your own or the recipient’s compatible AI work from that selected evidence. You choose the sources, access and sharing window. ## How OpenDataRoom helps Market: Fundraising, investor-relations and information-pack owners Explain the changed definitions between two quarterly LP reports. Keep source documents organised in drops, like folders, and select named packs for each audience. OpenDataRoom manages access and request records; the recipient uses their own AI for analysis. Current AI tools return extracted text, not complete original files. - [MCP request ledger](/guides/mcp-request-ledger): Review requests received through an authorised connection and what the service prepared, without claiming visibility into the full conversation. - [Source access for your AI](/guides/ai-document-connection): Let a compatible AI list, search and read the supplied text. Ask it to cite the file and passage so you can check the answer. ### Workflow impact A reporting clarification for the next LP conversation. The reviewer can consult the selected evidence through one authorised connection, then check and use the result in their existing workflow. ### Bring these documents - Selected reporting requests.csv - Q3 definitions.md - Reporting clarification.md ### Prompt for your own compatible AI Using only this approved pack, explain the changed definitions between two quarterly LP reports. Start with this source question: What neutral follow-up is supported by these reporting requests? Cite the file and passage. Distinguish supplied facts, assumptions, missing evidence and contrary evidence. Do not infer human reading or investment intent from request records. Try the fictional source question on this page and check the cited evidence. To use your own documents, check compatibility and join the waiting list; private access is by invitation. ## Frequently asked questions ### Can I rank LP engagement from the number of requests? No. An AI can make several automatic requests, and the ledger does not show human reading, satisfaction or intent. Use records to identify possible clarification work. ### What if a search returned no matches? Check the wording and extracted text first. Literal search may miss a synonym; do not assert that the reporting pack lacks information solely from a no-match result. ### Can the ledger tell me whether an investor intends to proceed? It can show the tool requests received through an authorised connection, the source references requested and the response preparation outcomes. Those records can inform a useful clarification or follow-up. They do not prove that the investor personally read a result, that an AI relied on it, or that an investment decision was made. An AI app may issue several requests automatically. ### How does the recipient connect, and who gets access? Choose your own AI or invite the intended email recipient. For a private invitation, the recipient verifies the authorised email and completes the required approval flow, then adds the connection in a compatible AI app’s settings. Forwarding an invitation alone does not authorise a different email. Permission covers the selected pack; create separate packs when audiences may see different documents. ### Can I keep the files and end someone’s access? Your wallet contains source drops, like folders. Each named pack shares selected files or passages from one drop. The source drop and its access packs have separate deadlines. You can keep the source until its displayed retention deadline while ending a recipient’s future access. Choose a sharing window, revoke it earlier when needed, and approve an extension deliberately. Expiry cannot recall material that an AI app or recipient has already retrieved. ### What happens when I update or remove a file? After you review and accept a drop update, fresh authorised requests receive the current versions of files already selected for their packs. This does not force an AI to fetch the files again or refresh its existing chat context. New files do not join those packs automatically. Review changed selected passages explicitly. Removing a file or its permission stops future retrieval, and access-change notices are queued for affected recipients. Provider acceptance is not proof of inbox delivery. This cannot erase content already retrieved. ### What if my files or AI app are not supported? Check the compatibility guide and try the public service-information sample first. An app must support the required MCP connection and authorisation; pasting a URL into ordinary chat does not install it. Use supported text-based files and inspect the preparation report. Originals are retained in encrypted storage, but the current AI tools return extracted text, not complete original files. Charts, images and layout are not faithfully delivered by those tools. Image-only scans and standalone images are refused; no OCR, audio transcription or spreadsheet recalculation is provided. Current pilot limits are listed on the pricing page. ### What information is recorded about use of the pack? The ledger records requests received by the service, authorised connection references, requested source information and preparation outcomes. Recipients can also deliberately submit a request, comment or note after approving the exact text. The owner sees that message, the verified connection identity and time in Recipient inbox for up to 90 days, unless deleted sooner. Received does not mean read or answered; no agent or automatic research is started. It does not record the entire AI conversation. Search text is supplied by the AI and may differ from the human question. An AI can reuse retrieved material without making another request. Literal search can miss relevant material; neither a search nor a file request proves that the AI reviewed the entire pack. Owners can investigate no-match searches before deciding whether to clarify wording, repair extraction or add information. A no-match result alone is not proof that a document is missing. ### Who can read my files in the hosted connection? Private-library file names and contents are encrypted in the browser with your wallet key. A hosted AI connection uses a separate access copy that you approve and that the service can decrypt for authorised retrieval. The receiving AI gets the content it retrieves and applies its own data policies. An optional desktop connector can decrypt locally, but it requires installation and is not a universal mobile connection. Review the security and compatibility pages before choosing a route. ## Your working output A reporting clarification for the next LP conversation ## Before you share 1. Bring the approved, dated versions of: Selected reporting requests.csv, Q3 definitions.md, Reporting clarification.md. 2. Check the readable text, source dates and permitted audience. 3. Choose your own compatible AI or invite the intended recipient with an appropriate access deadline. 4. Check the result against the source before using it; retain open questions rather than filling gaps. ## Fictional example documents These are invented teaching documents, not customer evidence. ### Selected reporting requests.csv Fictional R41, 9 October: search uncalled commitments, response prepared with no literal matches. R42: read Q3 definitions.md, response prepared. No private chat is included. ### Q3 definitions.md The report uses remaining commitments for amounts not yet called, subject to the stated recycling treatment. ### Reporting clarification.md Owner response, 10 October: points to remaining commitments in Q3 definitions and asks which period the reviewer needs. ## A source question What neutral follow-up is supported by these reporting requests? Illustrative answer: Offer the remaining-commitments definition and ask which period needs clarification. A wording mismatch can explain the no-match result. Do not infer the LP’s investment plans or that the returned definition was read. ## Turn a visible request into a careful clarification Review the request's reporting context and source references before preparing an answer. Confirm the approved report period and keep the operational request record separate from your marketing measures. ## Sources and further reading ## Related workflows - https://opendataroom.com/guides/lp-reporting-information-gap-clarification - https://opendataroom.com/guides/ic-evidence-requests-from-ledger - https://opendataroom.com/guides/ddq-gaps-from-requests Turn a visible request into a careful clarification. Start with the fictional documents on this page; no login is needed. For a real AI connection, try the separate public service-information sample before requesting private access. Admission is by invitation. Join the waiting list: https://opendataroom.com/signup Check compatibility and the separate public service-information sample: https://opendataroom.com/compatibility ## Try the fictional example https://opendataroom.com/example-demo.html?example=lp-reporting-questions-from-ledger