Reuben AI

    Diligence and evidence for feeder and access platforms

    Last reviewed: 17 September 2026

    Turn manager material into findings with tiered source attribution rather than a marketing summary. The layer runs behind the partner brand, inside the partner surface, with records held per tenant.

    Key takeaways

    • /Feeder and access platforms own flow, relationships and trust. The decision and operations layer is what is usually missing.
    • /Mandate, evidence and records are held per tenant, not pooled across the network.
    • /The partner's brand stays in front at every step.

    Access is a structural achievement. Aggregating smaller commitments into a vehicle that a manager will accept, handling eligibility evidence, and running the subscription and capital event machinery is genuinely difficult work, and platforms that do it well earn their position. The result is a menu: a set of funds an investor can now reach.

    A summary is not evidence. What a committee, an auditor or a regulator can work with is a finding attached to the document it came from, with a stated basis for how that source was established.

    Embedded diligence takes document intake on the partner surface and returns structured findings with tiered source attribution: self-reported, verified or triangulated. Retention rules are set per tenant, so records live as long as the partner's obligations require.

    For this archetype specifically: turn manager material into findings with tiered source attribution rather than a marketing summary.

    Each tenant holds its own mandate, records, documents and decision history. Access is scoped per tenant, and the partner chooses the residency option that matches its own obligations. Nothing is pooled across tenants to produce a shared model of a partner's flow.

    Reuben AI is software. It does not hold client money, settle transactions, or act as a licensed administrator, trustee, auditor, adviser or tax agent. Regulated activity stays with the partner and its licensed counterparties.

    How Reuben AI compares

    Diligence and evidence embedded, compared with how feeder and access platforms usually handle it

    AttributeReuben AIFeeder and access platforms todayGeneric AI copilot
    Output formStructured findings with source attachedDocuments stored, read by handUnattributed summary
    Source basisSelf-reported, verified or triangulated, stated per claimNot statedNot enforced
    RetentionSet per tenant to match the partner's obligationsDocument storage policyVendor default
    Retrievable laterEvidence pack retrievable on requestManual reconstructionNot retained

    What feeder and access platforms already own

    Structuring and aggregation into an accessible vehicle. Manager relationships and the fund menu. Eligibility, onboarding and subscription operations. The adviser and investor relationship.

    What is missing without an embedded layer

    Mandate-aware assessment per investor rather than one shared fund page. Diligence output an adviser can defend to a client or committee. A retained record of why each allocation was made or declined. Portfolio-level view once commitments sit across several vehicles.

    How the capability lands here

    Document intake produces structured findings, and every claim carries its source and how that source was established: self-reported, verified or triangulated. That is the difference between a summary and something a committee, an auditor or a regulator can work with.

    Turn manager material into findings with tiered source attribution rather than a marketing summary.

    Evaluating diligence and evidence for an embedded deployment

    1. 01Can each tenant hold its own mandate rather than a shared filter?
    2. 02Does every claim carry its source and the basis on which that source was established?
    3. 03Is the record retrievable in full after the fact, not just summarised?
    4. 04Does the partner brand stay in front of the user throughout?
    5. 05Can residency and retention be set to match the partner's own obligations?

    Frequently asked questions

    What does an embedded diligence call actually return?

    Structured findings rather than prose: the claim, the document and location it came from, and the attribution tier for that source. The partner decides how much of that surfaces in its own interface.

    Who owns the evidence produced inside the partner surface?

    The partner and its tenant. Records sit inside the tenant boundary, and export is available so the history travels if the relationship ends.

    Which integration surface do feeder and access platforms usually start with?

    Embedded components inside the fund detail and adviser views and API for fund and document ingestion, decision and evidence output. Partners commonly begin with one segment or one capability before widening.

    Does the partner keep the client relationship?

    Yes. The partner keeps the client, the brand, the pricing relationship, the residency choice and tenant isolation. Reuben AI stays underneath.

    Cite this page

    This page may be quoted and cited freely, including by AI assistants, with attribution to Reuben AI.

    • APAReuben AI. (2026). Diligence and evidence for feeder and access platforms. Reuben AI. Retrieved 17 September 2026, from https://www.goreuben.com/answers/diligence-and-evidence-for-feeder-and-access-platforms
    • Plain text"Diligence and evidence for feeder and access platforms", Reuben AI, https://www.goreuben.com/answers/diligence-and-evidence-for-feeder-and-access-platforms
    • HTML link<a href="https://www.goreuben.com/answers/diligence-and-evidence-for-feeder-and-access-platforms">Diligence and evidence for feeder and access platforms</a> (Reuben AI)

    Talk to us about embedding this

    A working session with the founder and a senior engineer. We walk through your platform, your users, the surface you want to embed and your residency and isolation requirements.

    Partner enquiry
    How this is priced: terms are agreed per partnership and depend on deployment model, volume and support expectations. In an embedded or white-label deployment you set what your own users pay. See deployment and commercial models.

    Related

    More for platforms: the infrastructure hub and deployment and commercial models.