# Prepare Series A diligence documents for an investor’s AI Canonical: https://opendataroom.com/guides/series-a-diligence-pack Updated: 2026-10-17 Let a reviewer compare a growth claim with its dated supporting figures and definitions. Keep the current deck, metric definitions and unresolved reconciliation questions in one bounded pack. ## How OpenDataRoom helps Market: Startups, Venture capital, Growth investors Let a reviewer compare a growth claim with its dated supporting figures and definitions. 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. - [Reusable private packs](/guides/control-data-access-ai): Keep the selected documents together for repeat questions and later reviews, within the displayed retention period. - [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. - [Named recipients and separate packs](/guides/separate-packs-per-audience): Choose who can connect. Prepare separate packs when people are allowed to see different documents. ### Workflow impact A source-linked Series A diligence response. Keep the selected evidence available through one authorised connection instead of assembling another set of attachments for each question. ### Bring these documents - Series A deck.pdf - Customer metric definitions.xlsx - Diligence questions.docx ### Prompt for your own compatible AI Using only this approved pack, let a reviewer compare a growth claim with its dated supporting figures and definitions. Start with this source question: Are all 120 active accounts paying customers? 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 send the same pack to an introductory investor and a diligence lead? Prepare a limited introduction pack and a separate diligence pack. Select approved aggregates for each; do not include customer identities merely because they are in the source drop. ### Who corrects the growth figures? Your finance or operating lead corrects the source. Accept the update after reviewing affected packs, then ask for fresh retrieval; an earlier AI reply does not update itself. ### 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. ## Fictional example documents These are invented teaching documents, not customer evidence. ### Series A deck.pdf Fictional Cedar Studio describes 120 accounts as active at quarter end. ### Customer metric definitions.xlsx Illustrative definitions: 90 paying accounts plus 30 free trials. The figures are supplied example values, not recalculated formulas. ### Diligence questions.docx Open issue: the deck does not distinguish paying accounts from trials. Retention cohorts and signed customer references are absent. ## A source question Are all 120 active accounts paying customers? Illustrative answer: No. The example defines 90 paying accounts and 30 free trials. Keep the distinction in the review and request retention cohorts before drawing a growth conclusion. ## Separate paying customers from trials before investor review Reconcile the deck's active-account claim with the metric definitions. Keep the missing retention cohorts on the diligence list instead of asking AI to invent them. A due-diligence checklist is a starting point, not proof that the pack is complete. Supply approved aggregates instead of unnecessary customer-level personal data. ## Sources and further reading ## Related workflows - https://opendataroom.com/guides/investor-evidence-index - https://opendataroom.com/guides/seed-fundraising-evidence-pack - https://opendataroom.com/guides/financial-model-review-pack Separate paying customers from trials before investor review. 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=series-a-diligence-pack