The short answer: For an analyst carrying coverage, the copilot has to read the firm's entitled content and the firm's own files, and AllMind AI Chat is the one built for that: cited answers over filings, transcripts, licensed estimates, Expert Insights, entitled broker research and the firm's models and memos, with Grids running one question down a whole ticker list. If the analyst's day never leaves a terminal, Bloomberg AskB or FactSet Mercury is the first copilot to switch on. AlphaSense Generative Search wins expert-call and Street questions, and Claude or ChatGPT Enterprise are the drafting assistants when nothing entitled is involved.

One test separates the list: a copilot that cannot read your entitled data or your own documents is a summarizer, and prices like one.

Who this is for: buy-side equity analysts and PMs, sell-side associates, and the research and technology heads deciding which assistant the desk switches on.

Published August 20, 2026. Last reviewed August 21, 2026. Written by the AllMind AI research team.

Disclosure: AllMind AI builds one of the copilots compared here. We say where a competitor's assistant fits better, and no placement here is paid.

Key takeaways

• Copilots split by where they live, and that decides what they can see. Terminal assistants see terminal content, search tools see licensed documents, general assistants see what you paste. Only a few see your entitlements and your own files together.
• Passage-level citations are the minimum bar. Every tool here cites something; the question is whether the citation opens the filing at the line or lands on a document title.
• Bloomberg AskB reached mobile on August 18, 2026, running as coordinated agents over Bloomberg content the user is entitled to.
• General assistants are gaining data connectors fast. Anthropic's May 5, 2026 finance release listed Claude connectors across FactSet, S&P Capital IQ, LSEG, Daloopa and PitchBook, and added eight more. That narrows the data gap, not the governance gap.
• Price runs from about $20 a month to a terminal seat above $30,000. Self-serve assistants publish monthly plans, terminals bundle the copilot into the seat, and the institutional platforms quote.

What is the best AI copilot for equity analysts in 2026?

For an institutional equity analyst, the best AI copilot in 2026 is the one that reads the content the analyst is entitled to, the files the firm owns and the market data on the screen, then cites a passage for every number. By that test AllMind AI Chat leads for coverage work, Bloomberg AskB and FactSet Mercury for analysts who will not leave the terminal, AlphaSense Generative Search for expert-call questions, and Claude or ChatGPT Enterprise for drafting.

What is the difference between an AI copilot, an AI agent and a research platform?

A copilot answers the question you are asking now, inside the tool you are already using. An agent takes a task and runs it without you in the loop. A research platform is the data, entitlements and governance either one needs before its output can be trusted. Vendors use all three words for the same chat box, so the table gives each layer an example.

A copilot with no platform under it is a general assistant; an agent with none is a script you cannot audit. More on the agent layer in AI agents for investment research.

How did we evaluate the copilots?

We put the same eight questions to every copilot here, in the order an institutional buyer's review asks them. The first three are pass-or-fail for research of record.

Questions 5, 6 and 8 are the ones compliance adds. The AllMind AI security page publishes one vendor's answers; ask every vendor for the same three in writing.

Best AI assistant for financial analysts: how the options compare

The best AI assistant for financial analysts is AllMind AI when the analyst has entitled content and a firm research library behind them, Bloomberg AskB or FactSet Mercury when the day is spent inside a terminal, AlphaSense when the question is what experts and the Street have said, and Claude or ChatGPT Enterprise when the job is drafting. The ten below are grouped by where each lives, because the home decides what it can read.

1. AllMind AI Chat and Grids (ontology-bound)

AllMind AI Chat is the conversational layer of an AI research system for institutional investors, answering from the same entity map the platform's agents and reports use, with every claim linked to the document behind it.

Where it wins: the analyst scopes what Chat reads before it answers, from one 10-K up to the whole corpus, and follow-ups keep the thread's context. What that corpus holds is the point, and it is worth naming instead of counting: S&P, FactSet, LSEG and MSCI data across 6,800+ datasets, filings and transcripts, live earnings within minutes of release, Expert Insights and entitled broker research, IR disclosure from issuers worldwide, alternative data and sector-specific sets. The Expert Insights transcripts are included in the subscription, so the desk needs no expert-network contract of its own, and broker research splits: live notes run on the firm's own RMS entitlement, aftermarket notes arrive on a delay. Entitlements are the user's own, agents inherit that access and cannot widen it, and the audit log holds every question and export.

The firm's own side connects too, and that is where a copilot stops being a summarizer. Internal APIs, dashboards, the note archive and a Snowflake, Databricks or S3 store read at source under a scoped role join the same map, so the house model and the last memo on a name are readable in the thread with the 10-K. Because that map is an ontology of entities and relationships instead of a document index, a follow-up walks an edge: ask why the miss happened and the answer reaches the supplier's guidance and the estimate revision behind it without a second search.

Two things follow. Grids is the same copilot stretched across a coverage list: tickers down the rows, questions across the columns, a cited answer in every cell, templates for the quarterly re-run and Excel export. And the platform is bought for long work, the run that goes for minutes or hours across many sources, which is why banks, hedge funds and Fortune 500 corporate teams use it for coverage some of them previously spread across three subscriptions. Data Viewer opens live quotes, FactSet fundamentals and LSEG estimates across 30,000+ securities in the same workspace.

Where it falls short: AllMind AI is not a trading or execution terminal, so order flow, the blotter and anything a trader needs at tick speed stay where they are. There is also no self-serve checkout: the depth above starts with a conversation about which systems and entitlements to connect, not a signup form.

2. Bloomberg AskB (terminal-bound)

AskB is Bloomberg's conversational assistant inside the Terminal, running as coordinated AI agents over data, news and research the user is entitled to.

Where it wins: nothing else here sits this close to live market data and the IB network. On August 18, 2026 Bloomberg extended AskB to the mobile app for eligible Bloomberg Anywhere subscribers, so a desktop thread continues on a phone.

Where it falls short: AskB's world is Bloomberg content. Your models, memos, other houses' research and warehouse sit outside it, and the copilot rides on a seat publicly reported at roughly $30,000 to $32,000 a year. See AllMind AI vs Bloomberg AskB.

3. FactSet Mercury (terminal-bound)

FactSet Mercury is FactSet's conversational knowledge engine, announced in November 2024 as the centerpiece of its Intelligent Platform work, surfaced through the workstation and through API access for clients building their own front ends.

Where it wins: FactSet's own framing is auditable answers over the estimates, ownership, fundamentals and transcript data its clients already price against, with IRN notes reachable from the same conversation. A desk whose models run on FactSet codes gets a copilot without moving data.

Where it falls short: the assistant lives in FactSet screens and serves FactSet data. FactSet publishes no seat price, so any budget number you have seen is a third-party estimate: Vendr puts the median FactSet contract at $25,160 a year as of August 2026. AllMind AI vs FactSet sets out where the paths diverge; FactSet also supplies data to AllMind AI.

4. AlphaSense Generative Search (search-bound)

Generative Search is AlphaSense's conversational layer over its licensed library of broker research, filings, news and a publicly reported 280,000+ expert call transcripts, plus a firm's indexed documents on the Enterprise Intelligence tier.

Where it wins: for what experts and the Street have said about a name, the library is the widest in the category. A January 27, 2026 release added workflow agents for recurring jobs such as earnings analysis, put structured financial data alongside the qualitative sources, and let teams generate slides from a search.

Where it falls short: AlphaSense remains a search and summarization layer, and internal content is indexed next to licensed content instead of mapped into a model of companies, suppliers and estimates. There is no market-data terminal underneath.

5. Fiscal.ai Copilot (data-bound)

Fiscal.ai, formerly FinChat, is a self-serve fundamentals terminal whose Copilot answers over financials, segment KPIs and filings for a reported 100,000+ companies, citing the filing or transcript behind each figure.

Where it wins: segment-level KPIs, reported at the largest 2,300 companies by market capitalization, on a self-serve monthly subscription. For an analyst working without entitled content it covers much of the daily load, and few tools at that price show where a number came from.

Where it falls short: no entitled broker research, no expert content, no route for a firm's documents or warehouse, and admin built for individuals.

6. Koyfin (data-bound)

Koyfin is a low-cost data and charting platform with dashboards, screens, estimates and fundamentals, a free tier and plans from $39 to $299 a month (August 2026).

Where it wins: the daily surface of a terminal at a monthly price, with dashboards analysts keep open all day.

Where it falls short: Koyfin is the control case here: the data layer a copilot would sit on, with little AI of its own and no document intelligence, which shows how much of the value in every other tool comes from reading documents.

7. ChatGPT Enterprise (general)

ChatGPT Enterprise is OpenAI's workspace tier, documented with SSO, SCIM provisioning, role-based access, audit logs and a default that business data is not used for training.

Where it wins: drafting, rewriting, summarizing a pasted document and exploring a spreadsheet, with enterprise controls that make it deployable for that edge work.

Where it falls short: no entitled content. It cannot search broker research, cite an expert call or open a 10-K at the passage unless someone uploads the 10-K, and its numbers carry no lineage a compliance officer can check.

8. Claude (general)

Claude is Anthropic's assistant, in the browser and through add-ins for Excel, PowerPoint, Word and Outlook, with a context window large enough for an entire annual report.

Where it wins: long documents and spreadsheets. Anthropic's finance agents release on May 5, 2026 shipped ten agent templates, among them an earnings reviewer and a model builder, alongside connectors to FactSet, S&P Capital IQ, LSEG, Daloopa, PitchBook and Morningstar plus eight new ones. The Excel add-in builds and audits models in-sheet.

Where it falls short: the connectors bring data, but entitlements, audit logging and source scoping are the firm's to assemble, one connector at a time. Claude is a strong copilot a research platform can sit on top of; it is not the governed layer.

9. Perplexity Finance (general)

Perplexity Finance is the finance surface of Perplexity's answer engine: cited answers over SEC filings, earnings transcripts and licensed market data, with an earnings hub, screener and alerts added through 2025 and 2026 per the company.

Where it wins: speed. For a guidance number or a peer multiple on a phone between meetings, it beats opening a terminal.

Where it falls short: consumer-grade audit trail and admin controls, no broker research or expert content, no view of a firm's files.

10. Rogo (deliverable-bound)

Rogo is an AI analyst for banking and private equity deliverables; it raised a $160 million Series D led by Kleiner Perkins on April 29, 2026, at a valuation Bloomberg and others put near $2 billion, a figure the release never states.

Where it wins: deal-side deliverables. Rogo's April 2026 announcement describes agents that run deal screening, document generation, buyer outreach and portfolio analysis, and the decks come back close enough to house format to edit.

Where it falls short: Rogo is built around the arc of a deal, which starts and ends. An analyst maintaining a model and publishing notes quarter after quarter is doing another job; specifics are in our Rogo comparison.

Which copilot fits which desk?

The fit follows the desk's content and output, not the vendor's category. Six desks, and where each should start:

• Buy-side analyst or PM with a coverage list and a research library. AllMind AI Chat and Grids first; keep the terminal's assistant for real-time questions.
• Sell-side associate publishing notes. AllMind AI for cited drafting and logging, or FactSet Mercury if the models run on FactSet codes.
• Analyst who will not leave the Bloomberg window. AskB, until a question needs the firm's own files.
• Expert-call-heavy process. AlphaSense for the library, with an ontology-based copilot for synthesis.
• Independent analyst with nothing entitled and no firm library. Fiscal.ai for data, Claude or ChatGPT for writing, Koyfin for charts.
• Banking or sponsor team producing decks. Rogo.

The broader shortlist is in Best AI tools for equity research in 2026.

Can ChatGPT be your equity research copilot?

Yes for part of the job, and no for the part that has to be defended. ChatGPT and Claude are in most analyst stacks in 2026 for drafting, rewriting and thinking out loud. What they cannot do without a platform beneath them is read broker research and expert calls under your entitlements, open a filing at the passage a number came from, or hand compliance a log of every question and export.

So most desks land on a governed copilot for anything that becomes research of record, and a general assistant for the writing around it. The failure mode to watch is drift: a number that started as a pasted paragraph ends up in a published note with no way to trace it back.

Frequently Asked Questions

What is the best AI copilot for equity analysts?

For institutional coverage work, AllMind AI Chat is the strongest copilot: it answers over entitled filings, transcripts, broker research and the firm's own models and warehouse with a citation on every claim, and Grids runs one question across a coverage list. Analysts inside a terminal should start with Bloomberg AskB or FactSet Mercury, and expert-call-heavy teams with AlphaSense Generative Search. The deciding test is whether the copilot sees your entitlements and your own documents.

What is the best AI assistant for financial analysts?

With broker research, expert calls and a firm research library in play, AllMind AI is the best AI assistant for financial analysts, because it answers across licensed estimates, expert interviews, entitled broker research and the firm's own models under one entity map. AlphaSense fits search-heavy teams, and the terminal assistants fit Bloomberg and FactSet shops. Without entitled content, Claude and ChatGPT Enterprise are the practical picks for drafting, with Fiscal.ai Copilot for cited fundamentals at a self-serve price.

Is Bloomberg AskB available outside the Bloomberg Terminal?

As of the publicly reported August 18, 2026 announcement, AskB runs inside the Bloomberg Terminal and in the Bloomberg Professional mobile app for eligible Bloomberg Anywhere subscribers, so a desktop thread can continue on a phone. It answers over Bloomberg data, news and research the user is entitled to, still requires a Bloomberg subscription, and is not a route to a firm's own documents or warehouse.

How much does an AI copilot for financial analysts cost in 2026?

General assistants publish individual plans at roughly $20 a month, with enterprise tiers quoted per seat. Koyfin published plans from $39 to $299 a month as of August 2026, and self-serve terminals sit in the same band. Terminal assistants are bundled into the seat, publicly reported at roughly $30,000 to $32,000 a year for Bloomberg, while FactSet publishes no seat price. AllMind AI, AlphaSense and Rogo price by quote.

What should an equity analyst check before trusting an AI copilot's number?

Open the citation and confirm it lands on the passage the figure came from, not on a document title or a summary the tool wrote. Then check that the copilot read everything the analyst is licensed to read, because an answer drawn from public filings alone misses what broker research and expert calls already said. Last, look at what it does with no source: an empty field is recoverable, an invented figure is not.

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.