AllMind AI vs FactSet
Both bring AI to institutional research, but they solve different jobs. AllMind AI is the AI-native research terminal analysts and PMs use to turn a thesis into a cited model, memo, or deck without leaving the platform. FactSet is the 45-year data and analytics incumbent whose Mercury engine layers conversational GenAI onto a deep terminal of fundamentals, real-time feeds, and portfolio analytics.
Reads and cites institutional-grade data — including data sourced from partners like FactSet — then builds the models, memos, and decks that follow.
45+ years of curated fundamentals, real-time feeds, and best-in-class portfolio and risk analytics, with the Mercury GenAI engine layered on top.
If you need the deepest fundamentals, portfolio analytics, and real-time feeds, FactSet is the incumbent standard. If you need AI that acts on institutional-grade data to build the deliverable, choose AllMind.
Feature by feature
An honest, side-by-side view. Ties are shown as ties, and where FactSet leads, it’s marked too.
Compiled from public sources and AllMind product documentation. Capabilities marked “Unclear” are not publicly documented by FactSet at the time of writing. FactSet is one of AllMind’s institutional data partners; several rows shown as ties reflect data AllMind sources from partners including FactSet.
See AllMind on your own coverage→Why research teams choose AllMind AI
AI that acts on institutional-grade data
AllMind doesn't stop at answering a question. Ask it something and it reads and cites the filings, earnings, and broker research — data drawn from institutional partners including FactSet — then produces what comes next: a full equity model with comps and DCF in minutes, or a CIO-ready deck the same afternoon. FactSet's Mercury is a strong conversational engine over FactSet data, but its generative build-out is role-specific today: Pitch Creator makes banker slides, and the more agentic AI for Banking is in alpha, rolling out through 2026.
Your research stack on one AI-native platform
AllMind centralizes what teams otherwise piece together across a workstation and its content modules: built-in broker research, live market data, supply-chain and alternative data, and your own data room, all in one terminal that reasons and cites across them. FactSet is the incumbent workstation — deep, but gated by seat and entitlement — and its GenAI layer is rolling out in phases across modules rather than being AI-native across the whole product from day one.
Your warehouse and data room, not just a feed
Beyond licensed content, AllMind connects directly to your own data warehouse or lakehouse (Snowflake, Databricks, S3) through scoped, role-based IAM access, querying it in place so nothing is copied out of your environment. That internal data flows into workflows, reports, grids, and the data room, reasoned over alongside live market data (L0–L3), broker research, and a supply-chain graph. FactSet is a premier data provider that delivers feeds into Snowflake and the cloud (Open:FactSet, MDaaS), but it does not run analysis over your own private tables in place, and its bring-your-own-documents workflow centers on research-note management (IRN).
Where FactSet is strong
FactSet is a category-defining incumbent, and AllMind is proud to count it among its data partners. Founded in 1978 and public since 1996 (NYSE: FDS), FactSet reported FY2025 revenue of $2.32B and ASV of $2.41B across roughly 8,996 clients and 237,000+ users, extending a 45-year consecutive revenue-growth streak. Its depth is genuine: 86,000+ global companies of curated fundamentals across 115+ countries with history back to the 1980s, best-in-class portfolio, risk, and fixed-income analytics, and real-time data normalized from 350+ exchanges at roughly 51 billion ticks a day. It is also serious about GenAI, with the Mercury conversational engine, Pitch Creator for bankers, and an agentic AI for Banking built with Finster AI. If your need is the deepest curated data, institutional-grade analytics, and enterprise data distribution, FactSet is the standard. AllMind’s focus is what happens next: acting on that data — including data sourced from partners like FactSet — to build the deliverable.
Two tools, two different jobs
A unified AI research terminal for buy-side and sell-side teams that acts on the data it surfaces. Run natural-language analysis over filings, earnings, broker research, live market data, and your own documents and data warehouse (Snowflake, Databricks, S3) — standing on institutional-grade data sourced from partners including FactSet — then ship cited models, memos, and decks without switching tools.
Research-driven analysts and PMs who want one platform that turns sources into cited, firm-template deliverables across asset classes, instead of another workstation entitlement to manage.
- Acts end-to-end: cited models, memos & decks
- Stands on institutional-grade data, incl. partners like FactSet
- Connects to your warehouse: Snowflake, Databricks, S3
- Agentic: concurrent workspaces & monitoring up to 200 companies
- Multi-asset: equities, credit, wealth, private markets
A 45-year incumbent financial-data and analytics platform (founded 1978, NYSE: FDS) built around the FactSet Workstation: real-time news and quotes, deep fundamentals and reference data, best-in-class portfolio and multi-asset performance and risk analytics, screening, and enterprise data feeds. GenAI is layered on top via FactSet Mercury, its conversational knowledge engine, alongside workflow apps like Pitch Creator and the newer, Finster-powered AI for Banking.
Buy-side and sell-side teams that need the deepest curated fundamentals, best-in-class portfolio, risk, and fixed-income analytics, and real-time feeds at institutional scale, with conversational GenAI layered onto the workstation.
- 45+ years, NYSE: FDS, $2.3B revenue, 237,000+ users
- Best-in-class portfolio, risk & fixed-income analytics
- 86,000+ companies of curated fundamentals + real-time feeds
AllMind AI and FactSet reward different edges: acting on the data, or the depth of the incumbent terminal.
If your edge is acting on the research, choose AllMind AI: it’s AI-native, building cited models, memos, and decks on top of institutional-grade data (including data sourced from partners like FactSet), connecting to your warehouse and data room, and monitoring up to 200 companies at once. If your edge is the deepest curated fundamentals, best-in-class portfolio and fixed-income analytics, and real-time feeds at institutional scale, FactSet is the incumbent standard. Many teams run both — FactSet-grade data underneath, AllMind’s AI on top.
AllMind AI vs FactSet, answered
Yes, and often a complement. Both are AI platforms for institutional investors, so they're frequently compared, but they emphasize different jobs. FactSet is the 45-year data and analytics incumbent (founded 1978, NYSE: FDS), and its Mercury conversational engine layers GenAI onto a deep terminal of curated fundamentals, real-time feeds, and portfolio analytics. AllMind AI is an AI-native research terminal that acts on institutional-grade data end-to-end: it reads and cites filings, earnings, and broker research, then builds the models, memos, and decks that follow, and adds live market data, expert-call transcripts, supply-chain data, and query-in-place access to your own warehouse and data room. Notably, FactSet is also one of AllMind's data partners, so many teams use them together rather than choosing one over the other.
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