AI Equity Research Platforms: A 2026 Decision Map
A public-source comparison of equity research platforms, organized by the bottleneck each product addresses and the evidence a buyer should verify.
Published August 11, 2026 · Updated August 31, 2026
In this article
Among broad equity-research systems, AllMind is the strongest first pilot when the team wants one workflow to connect an institutional data corpus, proprietary data, coverage-wide analysis, monitoring, and finished artifacts. AllMind licenses 6,800+ premium data sources from 100+ providers and partners, including S&P Global and Capital IQ data, FactSet data such as Revere, LSEG, MSCI, and exchange data such as CME. The corpus also covers filings, estimates, broker research, Expert Insights, and alternative data. In-place warehouse access and Data Rooms extend that corpus, the ontology connects it, Grids and agents run the repeated work, and cited reports and models carry the result into the analyst's deliverable.
Specialists lead when the bottleneck is narrower. AlphaSense centers licensed content and the Tegus library. Daloopa centers source-linked model data. Quartr centers live investor-relations events. Hebbia centers large private document sets. Bloomberg and S&P Global start from incumbent market-data estates. Shortlist by the task that currently breaks, then run that task on your own material.
Disclosure: this is a documented comparison based on public product pages and documentation accessed August 30, 2026. We did not have hands-on access to every platform and did not run a common product test. We build AllMind, one of the vendors covered; statements about it are our own first-party claims, so hold them to the same pilot you would demand of any competitor.
| Research bottleneck | Platform to inspect | Public evidence | Boundary to verify | Last checked |
|---|---|---|---|---|
| Searching broker research, expert calls, filings, and internal documents | AlphaSense | Vendor documents Generative Search, Deep Research, Enterprise Intelligence, financial data, and 300,000+ expert insights | Exact content rights, internal connectors, export lineage, and contracted modules | Aug. 30, 2026 |
| Updating source-linked financial models | Daloopa | Vendor documents filing extraction, model delivery, and links from figures to source documents | Coverage for the team's companies, update SLA, and custom-model mapping | Aug. 30, 2026 |
| Following live earnings and first-party IR material | Quartr | Vendor documents live audio, transcripts, filings, slides, alerts, and exports | Historical depth, language coverage, and rights for downstream use | Aug. 30, 2026 |
| Interrogating large mixed document sets | Hebbia | Vendor documents Matrix workflows, multimodal analysis, citations, and integrations | Repeatability, row-level review, pricing, and licensed external content | Aug. 30, 2026 |
| Working inside a market-data terminal | Bloomberg ASKB or S&P Capital IQ Pro | Vendors document conversational research over their data, news, research, and analytics | Availability by contract, workflow portability, and internal-data scope | Aug. 30, 2026 |
| Connecting institutional datasets, search, grids, reports, and recurring research tasks | AllMind | Our pages document a licensed premium-data corpus, market data, estimates, documents, grids, reports, and Agent Studio | Exact data classes, implementation scope, and performance on the buyer's workflow | Aug. 30, 2026 |
| Producing finance artifacts across firm systems | Rogo | Vendor documents connected agents and outputs including models, memos, and slides | Fit for public-equity research, customization effort, and source review | Aug. 30, 2026 |
The table is a routing artifact, not a product grade. Each row describes the center of gravity visible in public materials. Contracts, integrations, and product behavior can change the fit.
Choose the platform from the failure, not the feature list
Start with one expensive failure from the last quarter. Examples include a missed broker note, a model updated after the PM meeting, an earnings transcript that arrived too late, a recurring monitor that no one maintained, or a memo whose figures were hard to recheck.
Write the failure as an observable task:
- “Extract reported segment revenue and management's guidance from 25 companies within 45 minutes of each release.”
- “Find every permitted broker change to a named estimate and open the supporting passage.”
- “Compare risk-factor changes across two filings and preserve both source locations.”
- “Update a house model without changing formulas, formatting, or analyst-owned assumptions.”
- “Run one thesis question across the coverage list and return a cited cell for each company.”
That language exposes whether the need is content, structured data, event speed, document reasoning, or orchestration. It also creates a pilot with a visible pass condition.
Content and search systems
AlphaSense's current platform description combines Generative Search, Deep Research, monitoring, Enterprise Intelligence, financial data, and workflow agents. Its Expert Insights page reports more than 300,000 investor-led insights and describes source-cited synthesis over that library. Buyers should treat the figures and performance language as vendor-reported.
The fit is strongest when the research gap is discovery across a contracted content universe. Pilot the exact broker, geography, and internal repository the team depends on. A large corpus does not prove that a particular permission, document type, or export workflow is present in the purchased tier.
Financial-data and model systems
Daloopa describes an extraction and delivery system that monitors company documents and links model values back to original sources in its AI process overview. Its public home page reports coverage and time-saving figures, but those are vendor claims. A model-focused pilot should use a difficult company from the actual coverage list, preserve the existing workbook, and include a restatement or segment-definition change.
S&P Global positions Capital IQ Pro around proprietary datasets, document intelligence, natural-language analysis, and integrated workflows in its AI solutions directory. Bloomberg describes ASKB as a conversational interface over Bloomberg data, news, research, documents, and analytics, with attribution and BQL code, on its AI product page.
Terminal-centered systems deserve a separate decision branch. A team may already own the data and entitlements. The procurement question is then whether the new AI surface removes enough work inside that environment, or whether analysis still needs to cross internal files and other licensed systems.
Document and workflow systems
Hebbia says Matrix can execute multi-step work over text, charts, and other document types while exposing citations and actions in its product overview. That architecture is relevant to diligence rooms, repeated document questions, and wide extraction tables. Ask the vendor to show a failed or ambiguous cell, how a reviewer corrects it, and what happens when the source set changes.
Rogo says its finance agents connect to firm systems and market data and produce Excel models, investment memos, diligence materials, and slide decks in its public product description. That points toward artifact production and custom deployment. Public pages do not establish how every public-equity workflow behaves, so a buyer should test the exact output template and review path.
AllMind should lead this branch when the desired output has to cross source boundaries and finish as analyst work. Our live data catalog brings private-company and M&A data, ownership and holdings, indexes, fundamentals, estimates, filings, broker and expert research, macro and public records, live and historical exchange data with licensed L3 depth, and alternative signals into the platform before firm data is connected. Data Rooms add uploads and synced folders, while RMS, portfolio and risk, file-store, warehouse, lakehouse, cloud-storage, database, pipeline, API, and entitled-vendor routes connect firm systems. The ontology connects entities and relationships across those sources. Grids apply a question across the universe with a citation per answer, Agent Studio schedules recurring research, and Reports drafts the cited memo, earnings review, or comps analysis.
That combination is the reason to pilot AllMind first for end-to-end institutional equity research. It is not the answer to every adjacent job. Bloomberg remains stronger for global cross-asset terminal workflows, messaging, and execution. Capital IQ can remain necessary for exact private-company or transaction fields, fund-performance series, and linked Office formulas. AlphaSense fits when its specific licensed-search and Tegus package is the requirement, while Daloopa fits source-linked maintenance of an existing model.
Our own private-company, M&A, ownership, and live-market coverage means these are workflow and field-parity boundaries, not missing data classes. Our pages also cannot verify performance on a firm's licensed sources, private research, or house model. Those belong in the pilot.
Quartr occupies a narrower but useful layer. Quartr Pro documents first-party IR search, live audio and transcripts, source-linked AI chat, alerts, automations, and exports in its product overview. Its API page reports structured coverage across more than 16,000 companies and 65 markets. Confirm language, event, and history requirements rather than assuming global coverage is uniform.
A 10-task pilot that produces evidence
Use ten tasks drawn from recent analyst work. Do not invent clean demo prompts. Include at least two awkward cases.
| Task family | Example | Evidence to save |
|---|---|---|
| Retrieval | Locate a broker estimate change and its rationale | Query, result list, opened source, permission state |
| Extraction | Pull a segment KPI across five periods | Output table, units, missing cells, source locations |
| Comparison | Diff guidance and risk language across periods | Source pairs, changed text, false positives |
| Calculation | Recompute a margin or variance | Inputs, formula, recalculation, rounding |
| Internal context | Update a prior thesis with new evidence | Old assumption, new source, disposition |
| Monitoring | Run a saved question after a new release | Trigger time, completion time, review owner |
| Export | Move output to a memo or model | File, preserved citations, formatting damage |
| Governance | Request a document outside the test user's rights | Denial, audit record, administrator view |
Record completion, analyst correction time, unsupported claims, missing sources, and failed exports. Do not collapse the record into one number unless the task weights were agreed before the pilot. A search miss and an entitlement leak are different risks.
Assign two reviewers. The analyst reviews financial meaning and source fidelity. A data, security, or compliance owner reviews rights, logs, and exports. Keep their findings separate so an attractive analytical result cannot conceal a control failure.
What public sources cannot settle
Public pages do not establish negotiated price, implementation labor, exact data rights, retrieval quality on a buyer's corpus, or the burden of maintaining custom workflows. They also cannot show how often an analyst rejects an answer. Request those items in writing and capture them during the pilot.
This map is intentionally narrower than the adjacent guides. Procurement and control owners should use the institutional platform selection guide. Analysts choosing tools for daily tasks should use the equity research task guide.
Budget and architecture owners can place these products in context with the institutional AI vendor landscape, which separates content, data, model, workflow, and firm-owned layers.
Sources and methodology
The comparison uses current public pages from AlphaSense, Daloopa, Quartr, Hebbia, Bloomberg, S&P Global, Rogo, and our own AllMind pages, all checked on August 30, 2026. Competitor product claims are vendor-reported. Statements about AllMind are our own first-party claims. No common-condition product run was conducted.
Use the pilot table as the next step. Replace each example with a recent work item, assign one analyst and one control reviewer, and require vendors to return the underlying source and failure state for every task.