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Access is request-based: the homepage offers a Request Trial action that leads to a demo page, where institutional teams can ask for evaluation access. No self-serve trial is described.
Learn moreAllMind AI
AI equity research built on a connected financial ontology
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What is AllMind AI?
AllMind AI is an AI search tool. An institutional equity research terminal that links 6,800+ licensed data sources and a firm's own files through a financial ontology, with planning agents that draft memos, models and earnings notes and trace every number back to its source document.
AllMind AI is an AI-native research terminal aimed at institutional equity teams: asset managers, hedge funds, sell-side research desks and investor relations groups. Its core premise is that a general model will read whatever you hand it but has no idea what to fetch next, so AllMind supplies the connective layer. A financial ontology maps relationships across trillions of data points, linking suppliers to margins, broker estimates to coverage, and footnotes to the numbers they move. On top of that sit 6,800+ premium data sources licensed from more than 100 providers, including SEC filings, SEDAR+, exchange and venue feeds, broker research, FactSet, S&P Capital IQ, LSEG, MSCI and Third Bridge, plus a firm's own memos, models and private data. In practice the tool works in two modes. Simple lookups resolve in a single query. Larger requests are planned first: the research engine writes a plan, routes each part to the right source and finance-tuned model, then agents execute. Agents draft memos, models, comparable tables and earnings notes in a firm's own format, and one can hold a watchlist overnight and report what moved and why. The platform states agents can run for seconds, minutes, hours or days, and that a single answer may weigh millions of documents. Governance separates it from generic chat assistants. Entitlements follow the person asking rather than the agent, every question and export is logged, and firm data is not used to train models. Chat, reports, grids and the data room live in one workspace with sources still attached months later, and unsourceable fields are flagged rather than left looking current. It is not a self-serve tool. Pricing is not published, access starts with a trial request, and the value depends on your data entitlements and on encoding your own screens, metrics and gates. Buyers comparing against Bloomberg, AlphaSense or general LLM subscriptions should weigh the curated dataset and audit trail against the commitment of a sales-led onboarding.
How do you use AllMind AI?
1Request a trial and scope your data entitlements
Start on the demo page to request trial access. Expect a conversation about which licensed feeds and internal systems your firm can bring, since coverage follows entitlements.
2Understand the six layers of the platform
Review how the data engine, ontology, research engine, agents, permissions and governed workspace stack together. The ontology is the layer everything else depends on.
3Read the ontology explainer before your first query
The ontology page shows how relationships between companies, suppliers and estimates are mapped. Read it first so you know what the connected layer adds beyond a document search.
4Check the data catalogue against your coverage
The data page lists the licensed providers and feed types behind the platform. Compare it with the universe you cover to spot gaps before committing.
5Run a first request in the chat workspace
Once signed in, open chat and ask a plain-language question. Start narrow, such as a single metric or filing fact, then inspect the source document each answer traces back to.6Encode a recurring screen or gate
Move from one-off questions to repeatable work by setting your screens, metrics and gates as rules. The agent then runs them on your cadence and reports exceptions.
Pros and cons
Pros
- Ontology links suppliers, customers and estimates so margin changes surface across every affected nameAI
- Every figure traces to its source document with the calculation visible, and unsourceable fields are flaggedAI
- Research engine writes an execution plan before running, routing each part to the appropriate data and finance-tuned modelAI
- Permissions follow the person asking, exports are logged, and firm data is excluded from model trainingAI
- Chat, reports, grids and the data room share one governed workspace with sources retained over timeAI
Cons
- No public pricing and no self-serve signup, so evaluation requires a trial request and sales conversationAI
- Value is tied to which data entitlements a firm already holds, and the depth of licensed sources is not itemized per planAI
- Long-running agents that weigh millions of documents make answer latency and cost hard to predict upfrontAI
- Setup effort is real: screens, metrics and gates must be encoded before agents repeat a firm's process faithfullyAI
- No native mobile apps or public API are described on the homepage, which limits access away from the deskAI
How much does AllMind AI cost?
Support
Support runs through a contact page and a published FAQ resource for prospective and existing clients. No service tiers or response time commitments are stated on the homepage.
Learn moreIntegrations
Internal firm systems and proprietary structured and unstructured data join the same ontology as the licensed sources, alongside broker research routed by entitlement. No third-party app marketplace or public API is described.
Learn moreFeatures
A licensed data engine covering SEC, SEDAR+, 40+ exchange feeds, broker research, FactSet, S&P Capital IQ, LSEG, MSCI and Third Bridge; a financial ontology mapping relationships across sources; a research engine that plans complex requests; agents that draft memos, models, comp tables and earnings notes; watchlist monitoring; permissions, audit logging and a governed workspace.
Learn moreFrequently asked questions about AllMind AI
Does AllMind AI offer a free trial?
Access is request-based: the homepage offers a Request Trial action that leads to a demo page, where institutional teams can ask for evaluation access. No self-serve trial is described.How do you use AllMind AI?
The walkthrough on this page covers 6 steps: 1. Request a trial and scope your data entitlements 2. Understand the six layers of the platform 3. Read the ontology explainer before your first query 4. Check the data catalogue against your coverage 5. Run a first request in the chat workspace 6. Encode a recurring screen or gate.What platforms does AllMind AI support?
AllMind AI is available on Web App.What does AllMind AI integrate with?
Internal firm systems and proprietary structured and unstructured data join the same ontology as the licensed sources, alongside broker research routed by entitlement. No third-party app marketplace or public API is described.What are the limitations of AllMind AI?
No public pricing and no self-serve signup, so evaluation requires a trial request and sales conversation. Value is tied to which data entitlements a firm already holds, and the depth of licensed sources is not itemized per plan. Long-running agents that weigh millions of documents make answer latency and cost hard to predict upfront.
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Added10/21/2026
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