The short answer: if what you want off the terminal is deep research, the kind that crosses filings, estimates and your own models in one pass, AllMind AI is the alternative built for it. FactSet content is one of the sources it licenses, and it arrives connected to the rest through a financial ontology, so one agent works a question across every source. If the daily job is charts, screens and fundamentals on a budget, Koyfin replaces the screens from $468 a year and Fiscal.ai adds segment data at self-serve pricing. Almost nobody needs to leave FactSet data behind: the complaint is the terminal-shaped workflow and the seat cost.

Who this is for: asset managers, hedge funds, sell-side research desks and corporate IR teams reviewing a FactSet renewal or consolidating overlapping research subscriptions.

Published August 10, 2026. Last reviewed August 25, 2026. Written by the AllMind AI research team.

Reviewed by Anwaar Malik, founder of AllMind AI.

Updated August 25, 2026: added a worked example on Microsoft, expanded the competitor sections with dated product facts, and re-checked every price.

Disclosure: AllMind AI builds one of the platforms compared here, and FactSet is one of the AllMind AI data partners, which gives us an unusual perspective on this question. The comparison names where a competitor wins, and no vendor paid to be listed.

Key takeaways

• FactSet data is rarely the problem. AllMind AI licenses FactSet content alongside its other sources, so leaving the workstation does not mean leaving the numbers behind.
• Koyfin and Fiscal.ai replace the screens, and only the screens. Koyfin's published plans run $39 to $79 a month (July 2026), Fiscal.ai is self-serve, and neither carries entitled broker research or expert transcripts.
• Bloomberg Terminal and LSEG Workspace are sideways moves. Bloomberg is publicly reported at roughly $30,000 to $32,000 per seat per year (Investopedia, 2026), and both terminals leave the analysis in Excel beside the screens.
• AllMind AI is built for the deep end of the work. On the Microsoft example below, the capex line, the 10-K backlog note, each estimate revision and the desk's model are connected objects one agent works end to end.
• Governance, more than cost, carries the compliance case. AllMind AI holds a SOC 2 Type 2 report (November 2025), agents inherit each user's entitlements, every question and every export is logged, and nothing a firm sends trains a model.

Best alternatives to FactSet for AI research workflows: the 2026 shortlist

The shortlist splits into three groups. AllMind AI and AlphaSense take on the research work itself. Koyfin and Fiscal.ai replace the screens cheaply and leave the analysis to you. Bloomberg Terminal and LSEG Workspace swap FactSet for another terminal, which is rational when one dataset or the IB chat network drives the decision. The table gives best fit, core strength, internal-data support and the honest limitation for each; every cell carries a figure, a named feature or a specific gap.

Why do institutional teams look for FactSet alternatives?

FactSet is a financial data platform that delivers fundamentals, estimates, filings and analytics to research and portfolio teams through a per-seat workstation. Four complaints recur in renewal reviews.

• Cost per seat. FactSet quotes every workstation and publishes no seat price. Third-party estimates run from about $4,000 a year for entry access to $50,000 or more fully loaded, and Vendr's median FactSet contract is $25,160 a year (February 2026). FactSet's own disclosure is annual subscription value, about $10,000 per user including feeds and services at May 31, 2026.
• The workflow is the terminal. Data lives in screens while the analysis happens in Excel, Word and email. FactSet's own assistant, Mercury, has been in the workstation since December 2023 and answers over FactSet content inside it.
• Internal data is invisible. A firm's own models, memos, dashboards and warehouse tables do not exist inside the workstation, so the work that carries the house view sits outside the tool it is checked against.
• Coverage pressure. More names per analyst is a workflow problem, and no data feed solves it.

Our evaluation framework for picking an AI research tool scores those four against a shortlist.

How do the main FactSet alternatives compare, one by one?

Each platform below gets the same three parts, what it is, where it wins and where it falls short, and each is read against one live question on Microsoft (MSFT). The wider field, including Hebbia, Rogo, Daloopa and Quartr, is in Best AI Tools for Equity Research in 2026.

The test case. Microsoft's fiscal 2026 fourth-quarter earnings press release of July 29, 2026 reported quarterly revenue of $90.0 billion, up 18%, Microsoft Cloud revenue of $59.3 billion, up 27%, and Azure and other cloud services growth of 43%. Additions to property and equipment were $35.8 billion for the quarter, against $17.1 billion a year earlier, and $115.9 billion for the full year, against $64.6 billion in fiscal 2025. Commercial remaining performance obligation rose 84% to $678 billion. The 10-K for the year ended June 30, 2026 was filed the same day.

The analyst's question, as typed: Microsoft's FY26 capex was $115.9 billion, up about 80%, while Azure grew 43% and commercial RPO rose 84% to $678 billion. How much of next year's depreciation step-up is covered by contracted backlog, where does our model put Intelligent Cloud margin, and which brokers moved estimates after the print?

The FactSet workflow. The analyst pulls revenue, segment revenue and capex into Excel through the FactSet add-in, opens the 10-K in the filings viewer for the remaining performance obligation note, and reads consensus and its revision history on the estimates screen. Broker notes sit in the research portal under the firm's entitlements. The joining, the margin bridge and the comparison with the house model happen in the spreadsheet by hand, and the finished memo carries no link back to any of it. Mercury answers questions about FactSet content along the way, inside the workstation.

The AI research system. Every input is an object in one map: the capex line from the release, the backlog note in the 10-K, each estimate revision since July 29, the entitled broker notes, and the desk's own Microsoft model with its 2024 capex memo. One agent walks the question across those links and returns a memo in the desk's format, each figure opening the passage it came from with the calculation visible. The figures are the public ones above, joined and traced; the judgment on margin stays with the analyst.

AllMind AI

AllMind AI is an AI research system for institutional investors, built as a financial ontology, a maintained map of companies, suppliers, customers, estimates, filings and the firm's own research, with agents that move along those links.

Where it wins: the Microsoft question above is the shape of work it is built for. The agent starts at the capex line, follows the relationship to the backlog note and from there to each revision and each broker note, because the financial ontology stores those as linked entities and not as documents to be searched one at a time. The memo comes back in the desk's own format, and every figure in it carries its source passage and its calculation.

The half that terminal comparisons skip is your own material. Whatever the firm can expose joins that map: APIs, dashboards, document stores, and Snowflake, Databricks or S3 queried where they sit through an IAM role scoped to the tables it may read, so nothing is copied out of your environment. In the Microsoft case, the desk's model and its 2024 capex memo sit as entities beside the filing, so the agent can check this quarter's $115.9 billion against the ceiling the desk set then.

The licensed side is 6,800+ datasets across S&P Global, FactSet, LSEG and MSCI content, broker research, Expert Insights, investor-relations data, live earnings, alternative and sector data. Filings run across 40+ exchanges, and earnings figures land minutes after a print. The full AllMind AI vs FactSet comparison goes through that content line by line.

Where it falls short: AllMind AI streams no live quotes and has no execution or messaging function, so a desk that trades off the screen keeps a terminal for that, and any seat a certified compliance workflow depends on stays where it is. Pricing is quote-based with no self-serve plan, and the internal half of the map arrives after your own data owners connect the systems it reads.

AlphaSense

AlphaSense is a market-intelligence search platform built on licensed broker research, expert call transcripts, filings and news, expanded by its acquisition of Tegus, company-stated at $930 million and closed July 8, 2024.

Where it wins: the expert library runs to more than 280,000 investor-led call transcripts by the company's count, and on the Microsoft question it is where the desk looks for an operator's view of contract length behind that $678 billion backlog. Work Products, the PowerPoint and Excel assistants that shipped July 14, 2026, turn a set of documents into a deck or a sheet. The Enterprise Intelligence tier indexes SharePoint, Box and Google Drive, so the desk's own memos are searchable beside the licensed content.

Where it falls short: AlphaSense does not replace a market data terminal, so the capex and revenue series still come from FactSet or another feed. Internal documents are indexed for search beside the licensed content, so the check of the desk's model against the filing line stays in Excel. Pricing is quote-only; procurement tracker Vendr's median contract, a third-party estimate, is $17,500 a year across 38 deals (February 2026).

Koyfin

Koyfin is a low-cost data terminal for advisors and individual investors: charting, fundamentals, screening, transcripts and watchlists.

Where it wins: the published plans, dated July 27, 2026 on Koyfin's own plan page, run Plus at $39 a month, Premium at $79, Advisor Core at $209 and Advisor Pro at $299, with a free tier under them. On the Microsoft question it charts the capex series against Azure growth and opens the earnings transcript beside the chart, which covers what a generalist wants from a screen. Advisor Pro adds client reports, 200 a month across five portfolios, plus PDF statement upload for advisors building books.

Where it falls short: Koyfin is a data terminal with limited AI and no document intelligence, so the 10-K backlog note is a PDF you read yourself. There is no entitled broker research, no expert transcripts and no route for a firm's own models, which is where an institutional review stops. Teams pricing is custom.

Fiscal.ai

Fiscal.ai, formerly FinChat, is a fundamentals terminal and API with an AI copilot covering 100,000+ global public companies.

Where it wins: segment-level KPIs are the standout. Per its documentation, read August 25, 2026, segment and KPI data covers the 2,300 largest companies by market capitalization with 12+ annual and 24+ quarterly periods of history, so Microsoft's Intelligent Cloud line comes with the segment history behind it. Estimates, transcripts and ownership data sit beside the KPIs at self-serve pricing, and the API's free tier, 100 fixed companies at 250 calls a day with no card required, is enough to test a model-update script before paying.

Where it falls short: it is priced and built for self-serve users, so there is no entitled broker research, no expert-call content and no route for a firm's own models and memos. The copilot answers over Fiscal.ai's own data and documents, so the check against the house model and the desk's 2024 memo stays with the analyst.

Bloomberg Terminal

Bloomberg Terminal is the full-service market data and messaging terminal, publicly reported at roughly $30,000 to $32,000 per seat per year (Investopedia, 2026), with a lower rate on multi-terminal contracts.

Where it wins: real-time market data and the IB chat network are the two things a research platform does not replace, and where messaging is the workflow, that settles it. On the Microsoft question it is the screen that shows the after-hours move on the capex number and the chat where the sell-side desk explains it. AskB, the natural-language assistant over terminal data, entered beta in February 2026 and reached the mobile app on August 18, 2026.

Where it falls short: it sits at the top of the terminal price range, so a renewal fought on cost points elsewhere, and a terminal-resident assistant cannot reach a firm's own models, memos and warehouse, so the model-versus-filing check stays manual. Bloomberg AskB compared with AllMind AI works through that boundary.

LSEG Workspace

LSEG Workspace is LSEG's multi-asset terminal, the former Refinitiv Workspace renamed at the end of August 2023, publicly reported at roughly $10,000 to $22,000 per seat per year.

Where it wins: I/B/E/S estimates on 23,000 companies in 90 countries, Reuters News with more than 10,000 other sources, and research from nearly 1,300 contributing providers are the draw, per the product's data page in August 2026. On the Microsoft question that is where the desk reads the estimate revisions after July 29 and the broker consensus on fiscal 2027 capex. A Company Intelligence agent, launched in Workspace in July 2026, builds a company overview from financials, peers, deals, ownership and summaries of Reuters News and transcripts; a Microsoft Teams version is announced as coming.

Where it falls short: it swaps one terminal for another, so screens and data live in one place while the analysis happens in Excel and Word, and internal documents stay outside. The Company Intelligence overview is built from Workspace content, so the desk's own model and memo are still joined by hand. AllMind AI vs LSEG Workspace sets the two side by side.

What does a realistic 2026 research stack look like?

The stack that survives a compliance review in 2026 has three parts.

1. Keep fewer terminal seats, where live market data, execution or a certified compliance workflow demands them.
2. Run the research system as the one governed workspace holding licensed data, documents, internal knowledge and agents, with fundamentals, estimates and live market data in-product so dropping seats does not mean losing screens.
3. Keep Excel, fed by traceable data so nothing is re-keyed by hand.

One FactSet contract at the Vendr median ($25,160) plus one Bloomberg seat at the reported range ($30,000 to $32,000) is $55,000 to $57,000 a year before any research platform is added. In Substantive Research's July 16, 2026 survey of 35 large asset managers, 37% said onboarding takes four to six months and 69% named broker and data licensing the top barrier. Start the licensing conversation with FactSet, the brokers and the expert library on day one.

Run the research system beside the terminal for one full earnings season before any seat comes off, and use that season's memos, with their source links, as the evidence for compliance. AllMind AI does not publish client names and will arrange a reference call during an evaluation.

How do you make the case to compliance for leaving the terminal?

Lead with traceability and governance; cost comes second. AllMind AI holds a SOC 2 Type 2 report as of November 2025. An agent inherits the role of whoever ran it and can never widen it, every question and every export is logged, nothing your firm sends trains a model, and every model vendor in the path runs with no data retention.

Supervisory review gets easier too: every result opens the document at the relevant passage and every number carries its calculation, a better audit position than a spreadsheet cell typed by hand off a terminal screen. FINRA's 2026 oversight report (December 9, 2025) lists storing prompt and output logs among its effective practices for generative AI, and that is the log AllMind AI keeps for each question and each export.

Frequently Asked Questions

What is the best FactSet alternative for equity research?

AllMind AI is the FactSet alternative built for teams whose problem is the research workflow and not the data feed. It licenses FactSet content among its sources, joins the firm's own models and memos to that corpus through a financial ontology, and runs agents across that map. Koyfin fits advisors who mainly need charts and watchlists from $39 a month, and AlphaSense fits document search across broker notes and expert transcripts.

Does AllMind AI include FactSet data?

Yes. FactSet is one of the AllMind AI data partners, and SEC and SEDAR filings coverage comes through that partnership, connected through the financial ontology like every other source. Other licensed sources include S&P Global and LSEG content, plus filings from 40+ exchanges. Expert Insights transcripts are part of the subscription itself, and live broker research needs the firm's own research entitlement.

Can an AI research platform replace a FactSet terminal?

No. An AI research platform does not replace a FactSet terminal for live market data, real-time monitoring or a terminal-native workflow a compliance team has already certified. The practical split is to keep the seat where the desk trades or messages off the screen and move reading, synthesis and drafting first. An AI research system such as AllMind AI does that half with every figure traceable to the document behind it.

How much does a FactSet seat cost in 2026?

FactSet publishes no per-seat pricing, so every seat figure in circulation is a third-party estimate, running from about $4,000 a year for entry access to $50,000 or more fully loaded. Procurement tracker Vendr puts the median FactSet contract at $25,160 a year (February 2026), a whole contract and not a single seat. FactSet's own disclosure is annual subscription value of $2.48 billion across 247,766 users at May 31, 2026, about $10,000 per user including feeds and services. For comparison, Bloomberg Terminal is publicly reported at roughly $30,000 to $32,000 per seat per year, LSEG Workspace at roughly $10,000 to $22,000, and Koyfin at $468 to $948 a year.

How do I justify moving research off FactSet to compliance?

A compliance case for moving research off FactSet rests on traceability and governance, with cost second. AllMind AI holds a SOC 2 Type 2 report (November 2025), agents inherit the entitlements of the person asking and cannot widen them, every question and every export is logged, and nothing a firm sends trains a model. Put the audit log and the source-linked figures in front of compliance before the first pilot, and keep any seat that a certified terminal workflow depends on.

AllMind AI is the AI-native research platform for institutional equity teams. If you want proof on your own work, send us the workflow you want tested.