The short answer: for the research half of investor relations, peer prints, consensus and guidance benchmarks, transcript work across the peer group and the Q&A book, AllMind AI is the system built for it in 2026. It drafts the Street read from filings, transcripts and sell-side notes and joins that to the shareholder list and models the team already holds. The other half stays with IR-specific vendors: Q4 and Irwin for the CRM and targeting, Notified for the webcast and the IR site, Quartr for first-party documents, AlphaSense for searching analyst notes and expert calls. No single vendor does both halves.

Who this is for: heads of investor relations, IR managers and analysts, corporate communications and strategy teams at listed companies, and the IR advisory firms that run the quarter for several issuers at once.

Published August 28, 2026. Last reviewed August 28, 2026. Written by the AllMind AI research team.

Reviewed by Anwaar Malik, founder of AllMind AI.

Disclosure: AllMind AI builds one of the platforms compared here. We name the cases where an IR vendor fits better, we do not sell a CRM or a webcast, and no placement on this page was paid for.

Key takeaways

• AllMind AI is the research system for IR: peer prints read firm by firm, guidance benchmarks across comparables and transcript work across five months of calls, all from the public record.
• Q4 shipped an AI-native CRM in April 2026, with an agent it calls Q that logs meetings and builds briefing books over a database the company puts at more than 1,000,000 contacts.
• Irwin has been a FactSet company since October 2024; its 2026 survey of 223 IR professionals found 42 percent of IR teams actively using AI (vendor figure, no fieldwork date).
• Notified announced Agentic Event Reporting and AI Citation Reporting on June 8, 2026 for Q3 2026; the second shows how an IR website is cited inside ChatGPT and Claude.
• A general assistant handles one transcript: Claude's May 5, 2026 templates include a meeting preparer and an earnings reviewer, but neither ChatGPT nor Claude holds consensus history, sell-side notes or the meeting log.

Best AI tools for investor relations teams, by job

AllMind AI takes the research jobs, the peer reads, the consensus and guidance work, the transcript analysis and the Q&A book, and the IR-specific vendors take the CRM, the webcast and the website. The table sorts each tool by job, with a dated fact and a limit for each.

How we evaluated

Every tool was judged on four IR jobs: the peer read the morning after a print, consensus and guidance benchmarks, earnings script and Q&A preparation, and shareholder work. Each vendor claim carries a date and a source opened in August 2026: vendor pages and press releases for the IR vendors, a Bloomberg client letter reported by NeuGroup for the seat range, Anthropic's and OpenAI's own announcements for the general assistants. The worked example uses Nike's June 30, 2026 release and July 15, 2026 Form 10-K from EDGAR. Nothing below is presented as AllMind AI output.

How do IR teams use AI to monitor peers and consensus?

IR teams point an agent at a peer group and a question set, then read what comes back the morning after each print: the print against consensus, what management said, which analysts moved their numbers, and the read-through for their own company. AllMind AI runs that as a scheduled job across the peer group, with the sell-side notes on each peer read firm by firm and the transcript remarks filed under the quarter they refer to. Q4 and Irwin hold the consensus the company manages for its own name, and Quartr fires a prompt the moment a peer publishes.

Consensus work has two directions. Inbound, the team maintains the number the Street holds on the company, which the CRMs do well because the analyst list lives there. Outbound, the team benchmarks how comparables guided, resegmented or recast their numbers. AllMind AI builds that benchmark as a grid, comparables down the rows and disclosure questions across the columns, and where a company discloses nothing the cell says so. The guidance-change tracking method in the sibling piece applies to a peer group as much as a coverage list.

Worked example: Nike (NYSE: NKE), fiscal 2026 fourth quarter. The question, as an IR manager at a footwear peer would type it on July 1, 2026: what did Nike report, what explains the headline, and which lines will the Street ask us about?

Nike's release of June 30, 2026, furnished as Exhibit 99.1 to a Form 8-K, gives the figures. Fourth-quarter revenue was $10,972 million, down 1 percent reported and down 4 percent currency-neutral. Gross margin rose 890 basis points to 49.2 percent, and the release attributes roughly 900 basis points of that to a $986 million expected recovery of IEEPA tariffs. Diluted EPS was $0.72, of which $0.52 came from the same tariff item. Wholesale revenue was $6.6 billion, up 4 percent; NIKE Direct was $4.1 billion, down 7 percent; Greater China fell 12 percent reported. Inventories at May 31, 2026 were $7,501 million, flat on the year.

The headline EPS is unusable against any consensus until the $0.52 is stripped out, which leaves roughly $0.20 of underlying earnings on the release's own arithmetic. The lines a peer's board will ask about are the ones Nike's own IR team had to defend: a gross margin that is mostly a one-time recovery, direct revenue down while wholesale grew, and China at $5,847 million for the year against $6,586 million. The release carries no outlook section; guidance came on the 2:00 p.m. PT call, so the transcript and the sell-side's overnight rewrites are where the consensus gap gets explained.

Nike's Form 10-K, filed July 15, 2026, adds the full-year frame: revenue of $46,398 million, flat reported, and gross margin of 42.9 percent. A Form 8-K of June 23, 2026 announced a CFO transition effective August 17, which belongs in the peer file because the first call under a new CFO usually resets the guidance framework.

What each tool class does with those documents:

• The CRMs (Q4, Irwin) hold the peer's analyst list and consensus; Irwin's FactSet workstation shows the estimate revisions the next morning.
• Quartr's Automations run the team's standing prompt on the release and the call as they publish.
• AlphaSense returns the analyst notes and expert calls on Nike's China trend or the tariff recovery, ranked by relevance.
• A general assistant summarizes the pasted release from that file alone.
• AllMind AI reads the release, the call and the notes on Nike firm by firm in one run, files the guidance remarks under fiscal 2027, and lays the figures beside the peer team's own consensus file and Nike model, read in place in Snowflake, Databricks or S3.

The mechanism behind that last line is the ontology: Nike's Q4 call, the $986 million tariff item and the peer team's own margin thesis are stored as connected objects, so a question about tariff recoveries across the footwear group reaches the right passage without a search. Every figure above is the filing's, and none of it is AllMind AI output.

AI for earnings call preparation and Q&A prep for IR

Earnings preparation is the IR workflow where an AI system earns its place, because it reads everything the Street has said about the company and its peers before the script is written. AllMind AI restricts a run to earnings call transcripts and returns the pillars the Street keeps repeating, the numbers under each one, and the questions that came back a second time, with the firm that asked and the call it came from. AlphaSense's Anticipatory Q&A agent (August 5, 2026) predicts likely analyst questions from the same material, and Quartr's Q&A prep alerts flag peer questions as peers report.

The runbook below is the copyable artifact: T-10 through T+5 in business days, with the AI task at each step. It assumes a CRM (Q4 or Irwin), an events vendor (Notified or Q4) and one research system.

One rule makes the runbook safe: nothing pre-release goes into a tool at T-7 through T-1 unless the vendor's contract covers material non-public information. Every task above runs on the public record except the T-2 briefing books and the T+2 log, which live inside the CRM already. The T+5 retro is where a team learns whether the Q&A book earns its effort: record how many of the questions asked were in the book, and carry the misses into next quarter's candidate list. The buy-side view of the same days is in our earnings season preparation guide.

Which tools are IR CRMs and which are research systems?

Q4 and Irwin are IR CRMs with market data attached, Notified is an events and website platform adding research features, Quartr and AlphaSense are content platforms, and AllMind AI is a research system with no CRM. Buying two of the same category is the common mistake.

AllMind AI

AllMind AI is an AI research system for institutional teams, with corporate workflows built for IR teams and the advisory firms serving them. Its corpus covers SEC and SEDAR filings, earnings call transcripts, IR presentations and news, plus sell-side notes on the company and its peers under a coverage-relationship entitlement, the basis its research-access page lists for IR teams (August 2026). Expert Insights, expert-call transcripts included with the platform, reached customer use in August 2026.

Where it wins: long, multi-source jobs run from the public record. The Street read after a print comes back as one summary page and a firm-by-firm section behind it, every point opening to the note it came from; on a widely covered peer that is 35 to 40 analysts read in one run. Guidance benchmarking runs as a grid across comparables with change subscriptions, so the quarterly re-run is already built. The shareholder list exported from the CRM, and the model the team keeps, are read where they sit in Snowflake, Databricks or S3 through a connection the data team scopes once. Deliverables land in the team's own template.

Where it falls short: AllMind AI does not run an investor CRM, a webcast or an IR website, and it carries no 13F, holdings or ownership data, so targeting and surveillance stay with Q4, Irwin or the terminal. There is no self-serve checkout or monthly plan, and onboarding starts by scoping which internal systems to connect. Aftermarket sell-side research arrives on a delay that varies by broker. AllMind AI for corporates and investor relations shows the six workflows in detail.

Q4

Q4 is an IR Ops platform: investor websites, webcasting, an IR CRM, stock surveillance and consensus management for more than 2,600 brands including over half of the S&P 500 (company boilerplate, June 2026). In April 2026 (Business Wire, April 28) it announced AI-native CRM capabilities built around an agent it calls Q: meetings captured from chat or file upload, Outlook events turned into CRM records, AI-generated briefing books, natural-language queries of CRM data and sentiment analysis of the interaction history. On June 10, 2026 it added a Knowledge Base for approved materials, provenance guardrails on AI output and dedicated EU data residency.

Where it wins: the relationship record. Q4's investor database holds more than 1,000,000 contacts and institutions, refreshed quarterly (company-stated, April 2026), and Q works over the team's own meeting history, which no research system holds.

Where it falls short: Q answers from CRM data and the materials uploaded to its Knowledge Base. The 2026 releases name no filings corpus, no sell-side research and no peer transcript analysis, so the Street read and the guidance benchmark are built elsewhere and pasted in. Pricing is quote-only.

Irwin (a FactSet company)

Irwin is a Toronto-founded IR CRM that FactSet agreed to acquire on October 28, 2024, terms undisclosed. The combined product gives IR teams one login to the Irwin CRM and FactSet's Corporate Workstation: peer analysis, analyst estimates, earnings transcripts, ownership data, investor tear sheets that pair relationship history with holdings, and roadshow broadcast to 200,000+ buy-side investors and analysts through FactSet's network (company-stated, August 2026).

Where it wins: ownership and estimates in the same screen as the relationship record. A team that already runs FactSet for consensus gets the CRM without a second data contract. Irwin's 2026 State of Investor Relations survey of 223 IR professionals is also a useful adoption benchmark. It found 42 percent of IR teams actively using AI, 40 percent with a higher admin burden despite more tools, and 27 percent satisfied with data flow between tools (vendor survey, fieldwork date not stated).

Where it falls short: the AI is FactSet's terminal assistant working over FactSet content. Nothing on the Irwin page drafts the Street read firm by firm or benchmarks guidance across comparables. Pricing is quote-only.

Notified

Notified runs IR Hub: investor websites, webcasts, press releases and filings, and analytics, for 4,200+ companies (company-stated). On February 23, 2026 it added Market Intelligence to IR Hub, with competitor earnings transcripts live at launch and summaries, Q&A analysis and sentiment announced as coming; general availability was set for Q2 2026. At NIRI 2026 on June 8 it unveiled three more products for Q3 2026. Agentic Event Reporting produces AI summaries, key themes, Q&A analysis and media pickup after an event. AI Citation Reporting shows how the IR website is cited in AI engines such as ChatGPT and Claude. The third is a multilingual IR website chatbot.

Where it wins: the event and what happens to it afterward. AI Citation Reporting answers a question IR teams started asking in 2026: what does ChatGPT say when a retail investor asks about our company, and which page of ours did it read.

Where it falls short: Market Intelligence covers peer transcripts, and the analytic layers on top were announced as coming at launch. There is no consensus data, no CRM of its own and no sell-side research, so Notified is the events layer beside a CRM and a research system.

Quartr

Quartr is a first-party document platform: live calls, transcripts, slides and filings. Its IR use-case page (fetched August 28, 2026) states 16,000+ companies, 65+ markets and 50 million+ first-party documents; other Quartr pages showed 14,250+ and 15,000+ companies the same week, so the safe range is 14,000 to 16,000. For IR teams it offers AI chat over first-party material, peer benchmarking on messaging and KPIs, slide-history comparison, Q&A prep alerts, and Automations, launched August 24, 2026, which run a saved prompt when a company publishes. The page also names a Quartr MCP server for Claude and Codex.

Where it wins: speed on the peer's own words. The moment a peer posts its release and deck, the standing prompt runs, and the slide-history view shows which slide changed since last quarter, the fastest way to catch a KPI a peer quietly stopped disclosing. The mobile app is free.

Where it falls short: company-published material only. There are no sell-side notes, no expert calls and no ownership data, so the Street's reaction to the peer print comes from other tools. Pro and API are quote-only.

AlphaSense

AlphaSense is the market-intelligence search platform for sell-side research, expert calls, filings and news. Its IR article dated August 5, 2026 names an Anticipatory Q&A agent that predicts likely analyst questions, a Thematic Analysis of Analyst Q&A agent that tracks recurring themes across peer calls, custom Workflow Agents, and Wall Street Insights for tracking peer messaging and analyst reaction. The company states that its clients include 90 percent of the S&P 100, and its expert library stands at more than 300,000 transcripts (per its site, August 2026).

Where it wins: discovery across a library of roughly 300,000 expert transcripts and the broker notes the firm is entitled to. On a category shift, the search returns every sell-side and former-operator passage in seconds, and the Q&A agents give an IR team a second, independent prediction of what will be asked.

Where it falls short: the Street read is assembled by the reader from ranked results. Internal content enters through SharePoint, Box, Google Drive and Egnyte connectors (per its enterprise page, August 2026) and is indexed for search; a shareholder list arrives as an uploaded file, and there is no CRM or consensus management. Pricing is quote-only; the 38 contracts in Vendr's sample ran from $9,250 to $51,000 as of February 2026.

Bloomberg Terminal

Bloomberg is the reference terminal in many boardrooms, and for IR the relevant screens are estimates, ownership and holdings, and news. AskB, its assistant, entered beta in February 2026 and reached mobile on August 18, 2026, answering over terminal content. Seats are publicly reported at roughly $30,000 to $32,000 per seat per year with a multi-terminal discount and typically a two-year minimum (a Bloomberg client letter reported by NeuGroup in August 2022 is the primary source); Bloomberg itself publishes no price.

Where it wins: the number the board trusts. When a director asks what consensus is, the Bloomberg screen is what they expect to see, and the holdings screen is the quickest public view of who owns the company and its peers.

Where it falls short: the assistant stays inside the terminal, and the terminal holds none of the team's own material: no meeting log, no draft script, no perception-study transcripts. At the seat price, IR functions typically run one or two seats, so the terminal is the head of IR's lookup and the rest of the team works elsewhere.

ChatGPT and Claude

ChatGPT and Claude reach most IR teams through individual accounts before procurement sees them. Claude for Financial Services launched July 15, 2025, and on May 5, 2026 shipped ten finance agent templates, among them a meeting preparer and an earnings reviewer, plus Excel, PowerPoint and Word add-ins, with no published pricing. OpenAI's Deep Research launched February 2, 2025. Consumer and team plans run $20 to $200 per month per user (third-party reports of vendor pricing, 2026).

Where it wins: a single document and a first draft. Summarizing one peer transcript, tightening prepared remarks, or rehearsing a hostile question against public material are reasonable jobs for either.

Where it falls short: no consensus history, no sell-side notes, no meeting log, and no peer group watched between questions. Consumer plans are the wrong place for a draft release.

Shareholder and holdings analysis with AI

Holdings analysis is a CRM and terminal job, and the AI layer over it lives in Q4, Irwin and Bloomberg because that is where the ownership data sits. None of the research systems in this article, AllMind AI included, carry 13F or surveillance data of their own.

What a research system adds is the join. The team exports the shareholder list from the CRM into the warehouse it already runs, and AllMind AI reads that table where it sits, next to the peers' filings, the estimates and the notes. The question that becomes answerable is the one the CRM cannot ask: which of our top 50 holders also hold the peer that just cut guidance, and what did that management say about the driver we share. Banks, hedge funds and Fortune 500 corporates run that job on the same system from opposite sides of the table.

Can ChatGPT do IR work?

For one document and a public draft, yes; for the peer group, the consensus history and anything pre-release, no. Pasted material is all the assistant holds, so every task in the runbook above that needs the sell-side, the estimates or the meeting log fails at that boundary. The buy-side version of this question reaches the same answer for a 10-K.

Where a general assistant is the right tool: a small-cap IR manager with two covering analysts, rehearsing the script against the last two public calls, or a first pass over one peer transcript on a phone the morning of a print. Where it is the wrong tool: anything with a draft release in it, a guidance benchmark across eight comparables and four quarters, and any answer a board will see without a source behind each figure.

AI for investor relations: what to buy first and when to stay put

Buy in this order: keep the CRM you have, add or keep an events vendor, then decide whether the research half of the job is worth a system of its own.

The last decision has clear counter-cases. Stay with Q4 or Irwin alone if the IR function is one person whose quarter is meeting logistics and targeting, and the Street read is two analysts. Stay with Quartr plus a general assistant if the peer group is five names and nobody on the sell-side covers the company yet. Move the research half onto AllMind AI when the peer group is eight or more names, the sell-side is deep on you or on them, and the board expects the print against consensus, the analyst moves and the read-through the morning after.

Teams that make the third move typically retire a transcript subscription, a standalone sell-side aggregator and the manual precedent spreadsheet, because one run produces all three. The sentiment-tracking platform comparison and the consensus-data platform review cover the vendor overlaps, and the sibling piece on AI earnings-summary accuracy sets the error rates a Q&A book has to survive.

Frequently Asked Questions

What are the best AI tools for investor relations teams?

AllMind AI is the research system for IR teams that need the Street read on their own name and their peers drafted from filings, transcripts and sell-side notes, joined to the shareholder list and models the team already keeps. Q4 and Irwin (a FactSet company) are the IR CRMs, Notified runs the webcast and the IR site, Quartr is the first-party document layer and AlphaSense is the search platform for analyst notes and expert calls. An IR team of any size usually ends up with one CRM, one events vendor and one research system.

What is AI for investor relations used for day to day?

Four jobs fill most of the week: reading peer prints and the notes published on them, keeping consensus and guidance benchmarks current, preparing the earnings script and the Q&A book, and logging investor meetings into the CRM. Between quarters the same tools run a morning sweep of news and analyst notes on the company and its peers, and cut perception-study transcripts into themes. Targeting and holdings analysis stay in the CRM, where the ownership data lives.

Can ChatGPT do IR work?

ChatGPT and Claude draft well, and Claude shipped a meeting-preparer template and an earnings-reviewer template on May 5, 2026, so a single transcript or a pasted release is a reasonable job for either. Neither holds sell-side notes, consensus history or the firm's own meeting log, and neither watches a peer group between questions. Pasting a draft release or an unreleased number into a consumer plan is a disclosure problem, so most corporate policies limit both to public material.

Does AllMind AI replace an IR CRM such as Q4 or Irwin?

No. AllMind AI does not run an investor CRM, a webcast or an IR website, and it does not carry 13F or holdings data, so the CRM stays. What moves onto AllMind AI is the research half of the job: peer earnings reads firm by firm, consensus and guidance benchmarking, and transcript work across the peer group. The shareholder list the team exports from the CRM is read next to market data where that file already sits.

Is it safe to put a draft earnings release into an AI tool?

Treat a draft release or an unreleased number as material non-public information and keep it off consumer plans. Almost every IR research job runs on the public record, which is how AllMind AI positions its corporate workflows: the Street read, peer prints, precedent and guidance benchmarks need nothing of yours uploaded. For anything you do upload, ask the vendor for no training on customer data, encryption in transit and at rest, and a current SOC 2 report.

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.