Reuben AI

    Research and decisioning for feeder and access platforms

    Last reviewed: 17 September 2026

    Assess every fund on the menu against each investor or adviser mandate, and keep the reasoning. 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.

    Screening only helps when it reflects the user, not the platform. A single shared filter tells every participant the same thing about the same opportunity, which is exactly what a participant with a specific mandate cannot use.

    Embedded decisioning holds a written mandate per tenant. An opportunity arriving on the partner surface is assessed against that mandate, and the reasoning is retained with the assessment rather than discarded once the screen is shown.

    For this archetype specifically: assess every fund on the menu against each investor or adviser mandate, and keep the reasoning.

    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

    Research and decisioning embedded, compared with how feeder and access platforms usually handle it

    AttributeReuben AIFeeder and access platforms todayGeneric AI copilot
    Basis of the assessmentWritten mandate held per tenantShared filters and tagsPrompt text, no persistent mandate
    Reasoning retainedStored with the assessment and replayableNot capturedSession history only
    Whose brand the user seesThe partner'sThe partner'sThe vendor's
    Asset class breadth68 native asset classes, 314 sub-asset overlays across 56 of themWhatever the platform listsNo native rubric

    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

    Each tenant holds a written mandate. Opportunities are assessed against that mandate rather than a shared taxonomy, so two users looking at the same asset can receive different reasoning. Every score carries the inputs that produced it.

    Assess every fund on the menu against each investor or adviser mandate, and keep the reasoning.

    Evaluating research and decisioning 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

    Can each participant on a feeder and access platforms platform have a different mandate?

    Yes. Mandate is held per tenant, so two participants looking at the same opportunity can receive different output and different reasoning.

    Does the screening output show where a conclusion came from?

    Yes. Every score carries the inputs that produced it, and every claim carries its source and how that source was established: self-reported, verified or triangulated.

    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). Research and decisioning for feeder and access platforms. Reuben AI. Retrieved 17 September 2026, from https://www.goreuben.com/answers/research-and-decisioning-for-feeder-and-access-platforms
    • Plain text"Research and decisioning for feeder and access platforms", Reuben AI, https://www.goreuben.com/answers/research-and-decisioning-for-feeder-and-access-platforms
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    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.