Market Data, Filings and Expert Calls: A Platform Map
A rights-aware map of platforms that connect market data, filings, transcripts, expert content, and internal research, plus a request schema for vendor pilots.
Published August 20, 2026 · Updated August 31, 2026
In this article
No public source establishes one platform as the universal home for market data, filings, and expert calls. The practical choice is a rights architecture: identify the source of record for each content class, confirm what the AI layer may retrieve, and test whether citations survive a multi-source answer. A platform can display all three classes yet still fail if the contract excludes machine use, the timestamps are lost, or internal research cannot join the same entity.
This field guide uses public product pages checked on August 30, 2026. It does not report hands-on product testing. AllMind is our platform and it sits in this map, so our capability statements link to our own pages; verify them in a buyer's environment as you would any vendor's.
Start with five content classes, not one vendor count
"Market data" is too broad for a request for proposal. A last price, a point-in-time consensus snapshot, and a ten-year segment history have different owners, licenses, latency, and identifiers. "Expert calls" is also ambiguous. It may mean a searchable transcript library, a call arranged for the client, or transcripts the client already owns.
Define the required classes before inviting vendors:
| Content class | Minimum metadata | Rights question | Common failure |
|---|---|---|---|
| Market and reference data | instrument ID, venue, currency, timestamp, adjustment status | May the AI query and quote this feed? | A price is returned without venue or as-of time |
| Filings and issuer material | entity ID, accession or source URL, filing type, filed time, period | May documents be indexed, or only retrieved at query time? | The answer cites the filing title, not the passage |
| Consensus and broker research | measure, period, accounting basis, snapshot, entitlement | Does the user have display, extraction, and AI-use rights? | Current consensus is inserted into a historical question |
| Expert content | speaker role, interview date, company/topic mapping, transcript entitlement | Is this a library, an arranged call, or client-owned content? | A quotation loses speaker context or compliance restrictions |
| Internal research | document owner, version, permissions, issuer and thesis tags | Do permissions flow through retrieval and export? | A team note becomes visible to an unauthorized user |
This table is the real scope of the purchase. Document counts from different vendors cannot be compared cleanly because one may count pages, another transcripts, and another normalized time series.
How the platform families fit the map
Terminals begin with licensed market data
Bloomberg's public ASKB page says its assistant works across Bloomberg data, news, research, documents, and analytics, with attribution and underlying BQL for data analysis. The April 2026 ASKB roadmap also describes entitled expert intelligence, including Third Bridge content, plus planned integrations with proprietary firm knowledge. That makes Bloomberg a documented example of a terminal extending its licensed corpus into an AI surface. ASKB remains in beta according to Bloomberg's current product page.
FactSet is taking a similar data-first route. Its March 2026 Document Search release describes AI search over unstructured content, while its Portfolio Analytics MCP release focuses on governed performance, attribution, and risk outputs. Those pages support data and document workflows. They do not, by themselves, establish an expert-call library in every package.
S&P Capital IQ Pro documents structured fundamentals, estimates, ownership, transactions, news, filings, transcripts, and AI tools such as ChatIQ and Document Intelligence. Its current product page is strong evidence for those classes. It is not public evidence for an included expert-interview library, so a buyer should ask separately.
Research libraries begin with documents and expert content
AlphaSense says its Expert Insights collection contains roughly 300,000 investor-led transcripts and adds thousands monthly. That is a vendor-reported corpus figure, not an independent coverage audit. For an expert-heavy workflow, the useful pilot is not a count comparison. Select five niche topics, measure relevant transcript coverage, inspect speaker metadata, and verify the rights attached to quotations and exports.
An expert network's library is also different from its call service. GLG describes its library as on-demand expert content, while custom calls involve a separate sourcing and compliance process. The request for proposal should keep those deliverables in separate rows.
Cross-source research systems begin with the join
AllMind is the strongest first pilot when the unmet job is joining these content classes into one institutional research workflow. Our canonical data-source catalog documents live, delayed, and historical equities; OPRA options; futures and derivatives across CME, CBOT, NYMEX, COMEX, ICE, CFE, Eurex, and EEX; more than 40 exchange and venue feeds; and licensed L3 order-book data where permitted. The same catalog names SEC, SEDAR+, and global filings; included After Market Research; live broker research under the firm's entitlement; Aiera live calls; and Third Bridge Expert Insights. Our ontology is the entity and relationship layer that connects those sources with firm data, while Grids and Reports carry the joined evidence into coverage-wide analysis and a reviewable output. The buyer test is whether a licensed market metric, a filing passage, an expert observation, and an internal-model assumption resolve to one issuer and period without flattening their permissions.
AllMind is an institutional research system rather than an execution terminal or a stand-alone bulk-feed reseller, but that boundary should not be mistaken for missing market data. It carries live and historical exchange data, market depth, and L3 order books where licensed. After Market Research is included by default on a broker-specific delay; only live embargoed broker research uses the firm's own entitlement. A full internal-data setup requires a scoped onboarding conversation, and a team buying redistribution rights for a separate warehouse still needs the relevant data contract.
General assistants begin with connectors
A connector can make licensed content reachable, but it does not create the license. An enterprise assistant connected to a data vendor, document repository, or expert network can be a useful orchestration layer if the vendor returns stable identifiers, citations, timestamps, and permission decisions. The same assistant over copied exports may lose all four.
This distinction matters in demos. "Can the model answer from this source?" and "May this user use this source for this purpose?" are separate questions.
Use a source contract for every retrieved object
Give vendors a minimal source contract before the pilot. The exact field names may differ, but every answer should preserve the same concepts:
| Source-contract field | What the vendor should return |
|---|---|
| Entity | A stable issuer or instrument identifier |
| Content class | Market data, filing, estimate, expert material, or internal content |
| Source identity | Vendor record, accession number, or document ID |
| Timing | When the underlying event occurred, when it became available, and the fiscal or measurement period |
| Entitlement | Whether the source is included, licensed by the user, or owned by the client |
| Evidence location | Page, passage, row, or field that supports the answer |
| Transformation | Any normalization or calculation applied to the source value |
| Confidence status | Supported, partially supported, or unresolved |
This is a procurement artifact, not a claim that any vendor returns these exact keys today. Ask each vendor to map its native response to the schema. A blank or unsupported field is informative because it exposes where review is required.
A two-hop question tests more than a feature tour
Use a question that cannot be answered from one content class. For example:
For one covered issuer, compare the latest reported operating KPI with the consensus snapshot available immediately before the release. Then identify one expert observation and one internal assumption that could explain the variance.
The test packet should contain the issuer filing, timestamped consensus, one authorized expert transcript, and one internal note. Require the output to include:
- the reported KPI, period, unit, and filing passage;
- consensus value, snapshot time, contributor count if available, and source;
- arithmetic for the variance;
- expert quotation with speaker role and interview date;
- internal assumption with document owner and version;
- unresolved conflicts between sources;
- an access log showing which user's entitlements were applied.
Run the task once with all sources and once after revoking the expert-content entitlement. The second run should omit or clearly mark the restricted evidence. If it silently returns cached text, the system failed a permission test even if the answer is factually correct.
What to measure during the pilot
Keep four denominators:
- Retrieval coverage: relevant sources returned divided by relevant authorized sources in the test set.
- Passage precision: citations that land on supporting evidence divided by all citations opened.
- Temporal accuracy: values with correct as-of and fiscal period divided by all dated values.
- Permission accuracy: correct allow or deny decisions divided by all entitlement checks.
These metrics require a known test set. A vendor demonstration on unknown content cannot produce them. Record latency separately; a slow complete answer and a fast incomplete answer create different workflow costs.
Contract questions that product pages cannot answer
Ask the data owner and the AI-platform vendor to answer these in writing:
- Does the license allow indexing, vectorization, prompt-time retrieval, quotation, and model training? These are different uses.
- Is derived data owned by the client, the originator, or both?
- Can an answer be stored after the source entitlement expires?
- Which document and field identifiers remain stable across corrections?
- How quickly do filings, estimates, prices, and transcripts become available?
- Are expert transcripts approved for internal quotation, external publication, or neither?
- What audit record is available for access, prompt, source, transformation, and export?
The answers may force a multi-vendor architecture. That is not automatically a defect. A licensed terminal can remain the source of record, a research system can connect the work, and a general assistant can handle bounded drafting under the same permission model.
Limits of this platform map
Public documentation changes and packages differ by client. An unmentioned content class is not proof that a vendor lacks it. It means the class could not be established from the cited public page. Product availability, regions, beta status, and contractual AI rights must be confirmed in the proposed configuration.
The map also avoids comparing corpus counts as if they share a denominator. A fair evaluation uses a buyer-owned test set, known relevant sources, and written rights. That evidence is more useful than a table filled with unchecked green ticks.
Sources and methodology
- Bloomberg AI product page, ASKB scope, attribution, BQL, and beta status, accessed August 30, 2026.
- Bloomberg ASKB roadmap, entitled expert intelligence and roadmap integrations, April 16, 2026.
- FactSet AI-enabled Document Search release, March 26, 2026.
- S&P Capital IQ Pro product page, documented structured and document content.
- AlphaSense Expert Insights, vendor-reported transcript scope.
- SEC EDGAR APIs, primary-source filing identifiers and XBRL access.
For an AllMind evaluation, use the two-hop packet above and require the source-contract fields in the exported result. The useful deliverable is the raw evidence log, including denied access and unresolved joins, not a rehearsed answer alone.