AllMind AI vs Samaya AI
Both bring agentic AI to institutional research, both run deep, multi-step analysis, and both end in finished deliverables — but they take different routes. AllMind AI is the AI-native research terminal with owned, licensed data built in: 25+ brokers’ research, Third Bridge expert calls, and live market data that it reads, cites, and turns into models, memos, and decks. Samaya AI builds custom, finance-specific LLMs — a “lattice of experts” — deployed as agents that run over a firm’s own dispersed data.
Reads and cites filings, earnings, and 25+ brokers' research, then builds the models, memos, and decks — on owned, licensed data.
Purpose-built, finance-specific models in a "lattice of experts" deployed as agents that run over your firm's own filings, subscribed research, and internal documents.
Both run deep, agentic, long-horizon analysis. If your edge is frontier finance-specific models trained on your own proprietary corpus, choose Samaya. If it's a terminal that runs that deep research on owned, licensed data — brokers, expert calls, live market feeds — and ships the finished model, memo, or deck, choose AllMind.
Feature by feature
An honest, side-by-side view. Ties are shown as ties, and where Samaya AI leads, it’s marked too.
Compiled from public sources and AllMind product documentation. Capabilities marked “Unclear” are not publicly documented by Samaya AI at the time of writing.
See AllMind on your own coverage→Why research teams choose AllMind AI
The data is built in — brokers, expert calls, live market feeds
Samaya's agents are excellent over the data a firm brings and connects. AllMind ships the data itself: 25+ brokers' sell-side research, Third Bridge expert-call transcripts, live L0–L3 market data across 40+ exchanges, and FactSet, S&P Capital IQ, LSEG, and MSCI datasets — 250M+ documents in a published catalog. It reads and cites all of it, then builds the model, memo, or deck. Samaya does not ship its own licensed broker library, expert-call transcripts, or exchange market-data feed; a firm supplies that content.
One research terminal, not a model over your stack
AllMind is a full AI research terminal — search, live data, screening, grids, data rooms, and cited deliverables, all in one place. Its Deep Research mode runs long, multi-step analysis, and Agent Studio runs several such research agents at once — the same depth of autonomous, hours-long reasoning Samaya is built for. Samaya is a frontier model-and-agent company: its purpose-built LLMs run as agents over your own corpus and the research you subscribe to, which is powerful, but a firm still supplies the licensed content and live data feeds around it. With AllMind, the market stack and the workflow live together on one platform.
Multi-asset breadth and warehouse connectors
AllMind spans public equities, fixed income and credit, wealth, and private markets, and connects directly to your data warehouse — Snowflake, Databricks, S3, BigQuery — queried in place through scoped, role-based access so nothing leaves your environment. Samaya's public materials are equity-, banking-, and macro-centric; dedicated fixed-income coverage and customer-warehouse query-in-place connectors aren't publicly documented (Databricks is a Samaya investor). Where a capability isn't documented, we mark it Unclear rather than assume it.
Where Samaya AI is strong
Samaya is a serious frontier-AI company. Its founders come from Google Brain and Meta’s FAIR lab — CTO Fabio Petroni co-authored the original RAG paper, and CEO Maithra Raghu (ex-Google Brain) was named to the 2025 TIME100 AI list. Its differentiator is proprietary, finance-specific LLMs in a “lattice of experts” architecture, built to prioritize factuality over fluency with auditable reasoning. Samaya is deployed enterprise-wide at the top of the Street — Morgan Stanley across its Institutional Securities Group, plus a top-5 hedge fund and a top-5 asset manager — with thousands of users and a $43.5M Series A led by NEA (NVIDIA, Databricks, Eric Schmidt, Yann LeCun, and Jeff Dean among the backers). Novel capabilities like Causal World Models, a macroeconomic causal-reasoning agent, have no direct AllMind equivalent. If your edge is running frontier, purpose-built models as agents over your firm’s own proprietary corpus, Samaya is exceptional. AllMind’s focus is different: an AI terminal with owned, licensed data built in, across more asset classes, with a path for smaller teams.
Two tools, two different jobs
A unified AI research terminal for buy-side and sell-side teams that acts on the information it surfaces. Run natural-language analysis over filings, earnings, 25+ brokers’ research, live market data, and your own documents and data warehouse (Snowflake, Databricks, S3), then ship cited models, memos, and decks without switching tools.
Research-driven analysts and PMs who want one platform that turns owned, licensed data into cited, firm-template deliverables across asset classes — with a path for smaller teams, not just the largest institutions.
- Acts end-to-end: cited models, memos & decks
- Owned, licensed data: 25+ brokers, Third Bridge, live L0–L3
- Connects to your warehouse: Snowflake, Databricks, S3
- Multi-asset: equities, fixed income/credit, wealth, private markets
- 250M+ documents · 20+ sources · 40+ exchanges
An enterprise expert-AI-agent platform founded in 2022 by researchers from Google Brain, Meta FAIR, AWS, and the Allen Institute. Rather than a data terminal, Samaya builds proprietary, finance-specific LLMs and deploys them as agents that run over a firm’s own dispersed data — public filings, subscribed research, alternative data, and internal documents — to answer cited questions, synthesize reports, build models and presentations, and monitor markets.
The largest institutions — bulge-bracket banks and top-5 funds — that want frontier, purpose-built models operating as agents over their differentiated internal data, with enterprise-grade isolation and auditability.
- Custom finance-specific LLMs ("lattice of experts")
- Frontier-AI pedigree: ex-Google Brain & Meta FAIR founders
- Enterprise-wide at Morgan Stanley; top-5 hedge fund & asset manager
- Causal World Models for macroeconomic forecasting
AllMind AI and Samaya AI reward different edges: owned, licensed data in one terminal, or frontier custom models over your own corpus.
If your edge is an AI terminal with the data built in — 25+ brokers’ research, Third Bridge expert calls, live L0–L3 market data, warehouse connectors, and multi-asset breadth — that reads, cites, and builds cited models, memos, and decks, choose AllMind AI. If your edge is deploying frontier, finance-specific models as agents over your firm’s own proprietary corpus at the largest institutions, Samaya AI is the stronger fit.
AllMind AI vs Samaya AI, answered
Yes. Both are agentic AI platforms for institutional investors, and both build deliverables: cited answers, financial models, reports, and presentations. They emphasize different things. Samaya AI builds proprietary, finance-specific LLMs in a 'lattice of experts' architecture and deploys them as agents that run over a firm's own dispersed data. AllMind AI is an AI-native research terminal with owned, licensed data built in — 25+ brokers' sell-side research, Third Bridge expert-call transcripts, and live L0–L3 market data — that reads, cites, and turns those sources into models, memos, and decks. Teams that want the data built in, multi-asset breadth, and a path for smaller teams often choose AllMind; the largest institutions that want frontier custom models over their own proprietary corpus choose Samaya.
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