The short answer: the broker research your firm already pays for can go into an AI system under the entitlements you hold, but many agreements were written before machine reading was a question and say nothing about it. In a July 16, 2026 Substantive Research and Aiera survey of 35 large asset managers, 69% named licensing restrictions the top barrier to direct feeds. The path is an audit of each broker contract, an entitlement map by user, and a platform whose agents inherit that map. Live embargoed notes need your own research management system entitlement on any platform, AllMind AI included; aftermarket notes arrive on a delay that varies by broker.

Who this is for: heads of research and research operations at asset managers and hedge funds, chief compliance officers signing off on AI ingestion, and the data engineers asked to build the feed.

Published August 28, 2026. Last reviewed August 28, 2026. Written by the AllMind AI research team. Reviewed by Anwaar Malik, founder of AllMind AI.

Disclosure: AllMind AI builds one of the platforms compared here and carries broker research as an entitlement-gated data class. We name the cases where a feed vendor, a terminal or a general assistant is the better answer, and no placement was paid for.

How we evaluated: vendor claims were read on the vendor's own pages between August 24 and August 28, 2026; survey figures come from the publisher's release; the worked example uses Cisco's 8-K on sec.gov only, with no broker note quoted.

Key takeaways

• Licensing is the blocker, and the buy side says so. 69% of 35 large asset managers named broker and data licensing restrictions the top barrier to direct research feeds; 54% named compliance and entitlements (Substantive Research and Aiera, July 16, 2026).
• Broker research is the feed they want most. 77% ranked it the most valuable input to receive as a machine-readable feed into internal AI systems, ahead of earnings transcripts at 57% and market data at 42% (same survey).
• Onboarding runs a quarter or two. 37% said approving and onboarding took four to six months and 20% said more than six (same survey).
• Three timing tiers exist. Real-time notes need your entitlement, embargoed notes are the same notes held back, and aftermarket notes arrive on a delay that varies by broker with no entitlement required.
• The entitlement travels with the person. Agents that inherit the user's entitlement and cannot widen it are what a CCO can sign; a shared service account is what fails the review.

Broker research licensing for AI: why it is the buy side's biggest blocker in 2026

AllMind AI, Aiera, BlueMatrix and every other platform that carries sell-side notes runs into the same fact: a broker's research agreement was written for a person reading a PDF. It grants named users the right to receive notes, typically bars redistribution to third parties, and says nothing about a model that reads every note and answers questions from it. Feeding a note to an AI system touches redistribution, derived works and sometimes the user cap at once.

The July 16, 2026 Substantive Research and Aiera survey put numbers on it. 77% of the 35 asset managers had organization-wide generative AI deployments in place, and the same share ranked broker research the most valuable input to receive as a machine-readable feed. The gap between wanting the feed and having it is the licensing problem: 69% named broker and data licensing restrictions the top barrier, and 54% named compliance and entitlements. Gavin Skinner, COO of Aiera, said in the release that "today's licensing, entitlement, and compliance frameworks weren't designed for machine-readable, AI-driven environments."

Two things follow. The contract question comes before the vendor question, because a platform can only serve what your agreements permit. And the entitlement is a people question: a note licensed to the healthcare pod stays with that pod even when an agent does the reading. The primer on research management systems is in what broker research and RMS systems are and how to use them.

How broker research entitlements work: real-time, embargoed and aftermarket

A broker entitlement is a per-user permission, granted by the publishing broker, to receive a note at publication. Brokers grant it on a relationship: trading for buy-side clients, advisory for private equity and advisory firms, or coverage for investor relations teams, the three bases AllMind AI's research access page lists. The entitlement sits in the broker's system and the firm's research management system, and it names people, never machines.

Timing splits the same note into three products:

The delay matters for design. AllMind AI includes aftermarket research in its standard terminal with no entitlement of the firm's own, bars further distribution outside the terminal, and states that embargo periods vary by broker. A desk that needs the note the morning after a print connects its RMS so live notes read under its own entitlement; the mechanics are in integrating broker research and your RMS with AllMind AI.

Can we put sell-side research into ChatGPT or Claude?

Not by uploading the PDF, and yes through an entitlement-aware pipe. A standard research agreement bars passing notes to third parties, and OpenAI or Anthropic is a third party whatever its training terms say. Neither vendor's published retention position changes the contract between your firm and the broker. The upload box is the breach, and the easiest one to commit.

The compliant routes exist because the sell side built them. Aiera launched a consortium-backed content delivery platform on June 3, 2026, backed by eleven research providers including Bank of America, Barclays, Citi, Deutsche Bank, HSBC, Jefferies and UBS, with API and MCP connectors for Anthropic, OpenAI and Microsoft Azure (company-stated). BlueMatrix announced a partnership with Perplexity on January 13, 2026 that brings entitled broker research into Perplexity Enterprise, described at announcement as a pilot moving to private beta (company-stated). In both designs the broker's entitlement check happens in the pipe, and the assistant becomes a reading surface.

What the general assistant still lacks is the map. Each connector carries its own permissions, so a firm running five pods with five broker lists answers the entitlement question connector by connector, with no single record of who saw what. For a desk drafting from public filings the assistant is fine; see can ChatGPT analyze a 10-K for the test and the hedge fund compliance guide to ChatGPT for the policy.

How to get broker research into AI tools: a four-step path

Getting broker research into AI tools takes four steps, and the first two are paperwork. Budget a quarter for the sequence; 37% of surveyed managers took four to six months and 20% took longer.

1. Audit every broker agreement for AI language. Record whether each agreement addresses machine reading, derived works and redistribution, using the template later in this guide. An agreement silent on all three needs a written amendment before any note enters a pipeline; ask the broker's research sales desk whether it has a standard AI rider.
2. Map entitlements to users. Export the entitlement list from the RMS by user and by broker, then reconcile it against the people who will run the AI tool. Every mismatch is a note the tool must not serve.
3. Choose the ingestion route. Three exist: a feed vendor such as BlueMatrix or Aiera into your own stack, a research platform that connects to the RMS and reads under the mapped entitlements, or aftermarket content with no entitlement and a delay.
4. Prove inheritance before go-live. Run the tool as two users with different entitlements against the same query on the same name, and file the two answers with the access log. If both users get the same note, stop.

On AllMind AI the third and fourth steps are one mechanism. The ontology encodes entitlements alongside entities and relationships, so a restricted list or a deal wall maps to a role enforced in the graph; an agent inherits the role of whoever ran it, can never widen it, and each access lands in the log. Onboarding still opens with a data conversation about which systems and entitlements to connect, so a desk that wants a tool by Friday should start with aftermarket content and add the RMS connection once the entitlement map is signed off.

Machine-readable broker research feeds: who offers them today

Machine-readable broker research feeds are offered by the aggregators the sell side publishes through, by the research platforms that license notes, and since June 2026 by the brokers' own consortium. The table compares the routes on three questions: does the feed carry your entitlement, what arrives without one, and what the vendor publishes about scale.

AllMind AI

AllMind AI is an AI research system for institutional investors, with a financial ontology under the agents. The ontology page states that broker research, Expert Insights transcripts and market data come in under your entitlements, whether the firm already holds them or AllMind AI arranges them, and that aftermarket research is included on a delay with no entitlement of your own. The corpus spans S&P, FactSet, LSEG and MSCI data, broker research, Expert Insights, global investor-relations data and live earnings and financials, plus the firm's own files.

Where it wins: when the workflow is long and runs across licensed and internal data at once. A note read under the analyst's entitlement sits beside the filing, the transcript and the desk's own model, because Snowflake, Databricks and S3 connect through a scoped IAM role and are queried in place. The entitlement is enforced in the graph; an agent inherits the role of the person who ran it, cannot widen it during a run that lasts hours, and every access is logged. Banks, hedge funds and large corporates run it for that reason and have retired separate document search and transcript subscriptions in the process.

Where it falls short: live embargoed research needs the firm's own RMS entitlement, and the aftermarket delay differs by broker, so ask where your brokers sit before planning around it. There is no self-serve checkout, and a non-institutional user is better served by a self-serve tool.

BlueMatrix

BlueMatrix is the authoring and distribution system many sell-side firms publish through, which is why its buy-side product can deliver entitled notes from many brokers over one API. Its site states buy-side clients can access entitled research from up to roughly 600 sell-side providers through a single platform or API, and that its MCP server replaces bilateral integrations across 500+ providers (company-stated, August 2026).

Where it wins: for a data engineering team building its own retrieval stack. Centralized entitlement requests and approvals across brokers, a metadata-rich standardized format, and a January 13, 2026 Perplexity partnership show the direction.

Where it falls short: it is a pipe. There is no analysis workspace, no market data, and the Perplexity integration was a pilot moving to private beta at announcement. The firm still owns the entitlement map, the logging and the audit trail.

Aiera

Aiera began as an events and transcripts provider and is now consortium-owned: a $25 million Series B on June 9, 2025 from ten investment banks plus Third Bridge, then a content delivery and access platform launched June 3, 2026, backed by eleven research providers (company-stated). It states coverage of 45,000+ events a year across 13,000+ companies as of October 23, 2025.

Where it wins: as the sell side's own answer to machine-readable delivery. Because the publishing banks validate the content and sit on the cap table, entitlement enforcement happens where the broker wants it, with API and MCP connectors into Anthropic, OpenAI and Azure.

Where it falls short: it delivers content and does not analyze it, and it publishes no pricing; its /pricing address redirects to the homepage. Aiera is also a data provider to AllMind AI for live calls, which readers should weigh.

ChatGPT Enterprise and Claude for Financial Services

Claude for Financial Services launched July 15, 2025, added Aiera and Third Bridge connectors on October 27, 2025, and shipped ten finance agent templates on May 5, 2026 (company-stated). ChatGPT for Excel, announced in early March 2026, lists premium data providers that need the user's own entitlement (publicly reported, TechInformed).

Where it wins: drafting, code and reading public documents, and, through the Aiera or BlueMatrix routes above, reading entitled notes inside a tool the firm already licenses. Both vendors state a no-training default for commercial customers' data, which settles the model-vendor half of the compliance file.

Where it falls short: neither product holds a map of what each person may read across sources, and the upload box accepts anything. The fuller comparison is in ChatGPT, Claude and Perplexity vs institutional research platforms.

Broker research entitlements AI compliance: what to prove to your CCO

A chief compliance officer signs off on broker research in an AI system when three things are on file: the contract permits machine reading, the entitlement map matches the user list, and the tool cannot serve a note to someone outside that map. The template below is the first of those. Copy it into a spreadsheet, one row per broker agreement, and attach the clause text to each row.

BROKER AI-INGESTION CLAUSE AUDIT: [FIRM NAME]
Owner: Head of Research Operations | Reviewed by: CCO | Audit date: [DATE] | Next review: [DATE]

Column                       | What to record
-----------------------------|-------------------------------------------------------------
Broker                       | Legal entity on the agreement, not the sales contact
Agreement date / version     | Signed date; latest amendment date
Entitlement basis            | Trading / Advisory / Coverage relationship
Entitled users               | Named users or seat count; desks covered
Machine-reading clause       | Verbatim text, or "silent"
Derived-works clause         | Summaries, extracted figures, model inputs: permitted / barred / silent
Redistribution clause        | Third-party bar; internal-only; carve-outs for vendors
Named vendors permitted      | Platforms or aggregators the broker has approved in writing
Embargo period               | Days from real-time to wider release, per this broker
Aftermarket availability     | Yes / No; which platforms carry it
Machine-readable feed        | Yes / No; route (broker API, BlueMatrix, Aiera, RMS export)
Action                       | None / amendment requested / amendment signed / feed blocked
Amendment status and date    | Requested [DATE]; signed [DATE]

Example rows
Broker A | 2023-03-14 v2 | Trading | 12 named users, TMT and healthcare | silent | silent | third-party bar | none | 7 days | Yes | Yes, via RMS export | amendment requested | 2026-09-02
Broker B | 2025-11-20 v1 | Trading | 40 seats, all desks | "internal AI systems permitted" | permitted, internal | internal-only | two named platforms | 3 days | Yes | Yes, broker API | none | n/a
Broker C | 2022-06-01 v1 | Coverage | 3 named users, IR team | silent | barred | third-party bar | none | 10 days | No | No | feed blocked | 2026-09-15

FIVE QUESTIONS FOR THE AI VENDOR
1. Does an agent run as the user who launched it, and can it widen its scope during a run? (Pass: runs as the user; cannot widen.)
2. Where does the entitlement map live, and how is it synced from our RMS? (Pass: synced from the RMS on a stated schedule; no manual list.)
3. What does the access log record, and can we export it to our archive? (Pass: user, timestamp, document, query, export; scheduled export.)
4. Which brokers have approved your platform in writing, and can we see the list? (Pass: written list; our brokers on it or a path to add them.)
5. What arrives without our entitlement, and on what delay? (Pass: a per-broker answer, in writing.)

"Silent" in the machine-reading column is the common case for agreements that predate generative AI deployments, and it is what the survey's 69% describes. The fifth vendor question has a broker-specific answer on every platform, AllMind AI included. The controls behind the log, SOC 2 Type II and per-user scoping among them, are on the security page.

Worked example: Cisco's Q4 FY2026 print, seen from three desks

Cisco Systems (NASDAQ: CSCO) reported fourth-quarter and fiscal 2026 results on August 12, 2026 for the period ended July 25, 2026, in an 8-K on sec.gov. The question a technology analyst typed the next morning: what did Cisco report, what changed in AI infrastructure orders, and how does the Street read the FY2027 guide?

The public record answers the first two parts for every desk. Revenue was $17.3 billion, up 18% year over year; GAAP EPS was $0.97 and non-GAAP EPS $1.22. Total product orders rose 35%, or 25% excluding hyperscalers. AI infrastructure orders from hyperscalers were $4 billion in the quarter and $9.3 billion for fiscal 2026, with approximately $4 billion of revenue delivered in fiscal 2026 and $7.5 billion expected in fiscal 2027. Fiscal 2026 revenue was $63.3 billion, up 12%. Guidance for fiscal 2027 is revenue of $72.2 billion to $73.4 billion and non-GAAP EPS of $5.05 to $5.11, with Q1 FY2027 revenue of $18.0 billion to $18.2 billion.

The third part of the question separates the desks:

On AllMind AI the entitled desk's version runs as one workflow. The agent reads the 8-K and the transcript, pulls the notes its user is entitled to through the RMS connection, and joins the desk's own Cisco model from its warehouse under an IAM role the firm scopes, reading the table where it sits. That multi-source job, running for minutes over a print, is the case the platform is bought for. The unentitled desk gets the same filings and, later, the same notes on the aftermarket schedule, fine for a thesis review and wrong for the morning after. No note contents appear here because quoting one would be the breach this guide is about.

Frequently Asked Questions

What does broker research licensing for AI cover?

It covers three separate permissions: the right to receive a note, the right to load it into a machine that reads it on your behalf, and the right to keep derived output such as summaries and extracted numbers. An agreement written before generative AI reached the desk is often silent on the second and third. Platforms such as AllMind AI read live notes under the entitlement your firm already holds, so the second and third permissions are settled with the broker once and enforced per user afterward.

Does uploading a broker note to ChatGPT breach the broker's license?

Usually yes, because a standard research agreement bars redistribution to third parties, and a model vendor is a third party regardless of its training and retention terms. The breach is a contract matter with the broker, so the practical exposure is losing access or being asked to pay for enterprise redistribution rights. A firm that wants sell-side content inside a general assistant routes it through an entitlement-aware pipe such as Aiera's platform or BlueMatrix's API and keeps the chat tool as the reading surface.

How long is the aftermarket delay on broker research?

It varies by broker and by agreement, from a few days to well over a week after the note reaches real-time subscribers, and the period can change when a provider renegotiates. Aftermarket research needs no entitlement of your own, which is why platforms can include it in a standard subscription, and why it is unsuitable for trading decisions on the print itself. Ask each of your brokers where they sit before planning a workflow around it.

Do AI agents widen broker research entitlements?

They can, and this is the question a chief compliance officer should ask first. The failure pattern is an agent that runs under a service account with access to every desk's research feed, so an analyst on one pod receives a note licensed to another. The control to require is entitlement inheritance: the agent runs as the person who launched it, cannot widen its scope during a run, and every access is written to a log the firm can export.

How long does onboarding a broker research feed into an AI platform take?

In the Substantive Research and Aiera survey of 35 large asset managers published July 16, 2026, 37% said approving and onboarding took four to six months, 20% said more than six months and 17% said one to three months. The calendar time is mostly contract review, entitlement mapping and compliance sign-off, so a firm that audits its agreements before selecting a vendor takes the shorter path. The technical connection to a research management system is the shorter part of that calendar.

AllMind AI is the AI-native research platform for institutional equity teams. If you want proof on your own work, send us the workflow you want tested.