Ontology-poweredAI for equity research
6,000+ premium data sources and your firm’s own information, connected through one financial ontology layer that surfaces what your team didn’t know to look for.
Trusted by leading institutions for equity research.Trusted by leading institutions for public markets equity research.
- Fortune 100 E&P






Our platform powers in-depth AI equity research across buy-side, sell-side and corporate teams, from the first screen to the investment committee.
AllMind OS
Six layers, from licensed data to a governed workspace. The ontology is the second of them. is the second of them, and nothing above it works without it.
Data Engine
6,000+ premium sources and your firm's own structured and unstructured data, in one place.
- Data Engine. 6,000+ premium sources in one place, with your firm's own structured and unstructured data. Sources include SEC, SEDAR, 40+ Exchanges, Broker Research, FactSet, S&P Global, LSEG, MSCI, Expert Insights, Snowflake, Databricks, 6,000+ Datasets.
- Ontology & Relationships. A continuously evolving map of relationships connecting trillions of data points across internal and external sources.
- Research Engine. A price check takes one lookup. A diligence request takes a plan, written before any work runs: each part routed to the right data and the right finance-tuned model.
- AI Agents. Agents draft memos, models, comp tables and earnings notes in your firm's format. One holds a watchlist overnight and tells you what moved and why.
- Permissions & Audit. Entitlements follow the person asking, not the agent. Every question and every export is logged, and nothing your firm sends trains a model.
- Governed Workspace. Chat, reports, grids and the data room are one workspace, not four tools. Work stays where your team can find it, with its sources still attached a quarter later.
- AllMind. All six layers become one system. Ask in plain language, and what comes back traces to the document it came from.
Why Institutions Choose AllMind.
Public equity research, end to end. Built for asset managers, hedge funds, sell-side research desks and investor relations teams.
One place instead of fifteen
Filings, transcripts, entitled broker research, expert calls and the alt data your firm already pays for sit on one map, linked to each other rather than stored side by side. Your own memos and models are in there too.
premium sources, plus your firm's own information, all in one place.
It tells you when it doesn't know
Every number traces back to the document it came from, with the calculation behind it visible. When a field cannot be sourced it gets flagged, not left sitting there looking current.
traceable to the document it came from
Your process, encoded
Your screens, your metrics, your gates, your template become steps the agent repeats the same way every time. Set the rule once and it runs on your cadence, reporting the exceptions rather than another refreshed table.
run in your order, showing the calculation at each step
Depth without a ceiling
Agents run as long as the work takes, whether that is seconds, minutes, hours or days, holding everything they have read in view. A single answer can weigh millions of documents.
documents connected behind one answer.
Our Vision
Every research team we sit with has the same models we do. A model will read anything you hand it, and it has no idea what to hand itself. Ask which names you cover trace back to the same supplier, or which of your positions carry the exposure that just repriced, and the hard part is knowing where to look.
We built a continuously evolving market map that gives AI a connected layer to understand how everything fits together. It tracks which suppliers affect margins, which broker estimates connect to your research, and which footnotes move which numbers. That relationship layer is what we call ontology.
One managing director, with forty years in sell-side research, used to spend three weeks on a single initiation report. Most of that time went to rebuilding the links between a company, its key insights, and everything that touches it. He can start without having to learn or find those links himself. That is the vision: a connected layer that helps investment professionals focus on what matters most and go deep into the data efficiently. When a supplier pushes margins down, the change travels across every name it touches, often revealing the one nobody thought to check. You still make the call but AI handles the tedious part.

Anwaar Malik
Co-Founder & CEO, AllMind AI
Built by leading Quants, PhDs, AI Researchers, and Finance Professionals
Our team comes from asset management, research, and quantitative finance. Between us we have managed large institutional portfolios, published dozens of papers, and made sense of a lot of noisy, messy data.






Enterprise-GradeSecurity.
SOC2 II
Governance and Compliance
No training
on user data
Encrypted in
transit and at rest
Data encrypted at rest with AES 256 and in transit with TLS 1.3
