Fireflies.ai vs Otter.ai: Best AI Meeting Notes for Teams (2026)

For years, AI meeting assistants shipped the same product. An AI bot joined your call, transcribed it, and emailed a summary. That product is now table stakes. Fireflies, Otter, and the rest of the AI meeting assistant category compete on what happens after the transcript: workflows, agents, search, coaching, and CRM hygiene.

This guide compares Fireflies.ai and Otter.ai head to head on the things that decide whether a team adopts and keeps a meeting assistant. Capture method. Transcription accuracy. AI summaries. Search. Team collaboration. Conversation intelligence. Security. Price. It also flags where a third option, Grain, is a better fit for teams whose meeting workflow involves shareable video clips, coaching playlists, and go-to-market enablement.

Fireflies vs Otter in 2026

The category has moved past transcripts

Three years ago, "I want a tool to take notes for me" meant transcription. Today both Fireflies and Otter pitch themselves as something larger. Fireflies leads with conversation intelligence and AI agents. Otter relaunched in April 2026 as a "Conversational Knowledge Engine" that searches across multiple meetings and connected enterprise tools.

A clean meeting summary is no longer the differentiator. The tools that win turn meeting content into things a team can act on. A CRM record updated. A follow-up sent. A task assigned. A competitor mention flagged. A key moment shared with someone who wasn't on the call.

Teams describe the same set of pains across vendors. Follow-ups fall through. Handoffs lose context. Knowledge stays in one rep's head. Compliance gaps show up when sensitive sales calls get recorded without a policy. Fixing those is harder than producing a transcript. It's also where Fireflies and Otter diverge from each other, and where Grain is often the better answer.

How to read vendor claims

The category vocabulary has gotten loose. "AI agent" can mean a chatbot that drafts emails, a voice-activated AI assistant, or an autonomous workflow runner. "AI note taker" can mean real-time transcription or post-meeting recaps. "Conversation intelligence" historically meant analytics for sales managers. Today vendors apply the term to anything that searches a meeting library.

What matters for buyers isn't what the tool calls itself. It's what work happens after the meeting ends, and whether the tool reduces or adds to that work.

Fast buyer-fit snapshot: where does each AI note taker fit?

When Fireflies tends to win

High meeting volume orgs that need notes auto-routed to multiple downstream systems. Admins who want governance controls, role-based access, and audit trails. Teams running across many languages. Companies on HubSpot or Salesforce that want CRM updates from meetings without manual data entry.

Fireflies has the deeper integrations catalog and the more mature admin posture of the two products.

When Otter tends to win

Real-time transcription as the primary use case. Otter's live transcript UX has been its signature feature since launch. Smaller, English-speaking teams that want simplicity over configuration. Teams whose meeting output stays inside Otter rather than getting pushed downstream. Knowledge workers in back-to-back meetings who want to ask questions across past meetings without leaving the app.

Otter's recent Conversational Knowledge Engine launch added MCP client and server capabilities. Meeting data flows into ChatGPT or Claude. External tools (Gmail, Drive, Notion, Jira, Salesforce) flow into Otter AI Chat.

Where Grain fits

Go-to-market teams whose workflow includes shareable meeting highlights, coaching playlists, and team-wide enablement. Sales teams that need conversation intelligence with structured CRM writes, not notes pushed as activity records. Teams where a 90-second key moment is the unit of work, not a 60-minute recording or a paraphrased summary.

Neither Fireflies nor Otter is built around shareable video clips. Fireflies' Soundbites are audio-only. Otter doesn't focus on clips at all. If your workflow is "send the moment to someone who wasn't there," that's a Grain shape.

Try Grain free. Record, clip, and share your next meeting in minutes. grain.com/app/signup

Recording and capture methods that decide adoption

Both Fireflies and Otter use an AI bot to capture meetings. A virtual participant joins the call, captures audio (and in some cases video), and posts a summary afterward. Both rely on speech recognition that has improved sharply since 2023.

Bot-based capture across major platforms

Fireflies' AI bot joins Zoom and Microsoft Teams calls (plus Google Meet) based on calendar invites or meeting links. It works on any video conferencing platform where you can add a participant. There is no native in-app capture. Fireflies does not run as a desktop recorder.

OtterPilot covers the same major platforms. OtterPilot 3.0 added Visual Context, which captures slides and whiteboard sketches into the transcript at the timestamp they appeared. Otter also has strong native iOS, Android, and web apps for in-person voice conversations.

Both tools require participant awareness that an AI bot is in the room. That works for internal calls and most B2B sales conversations. It is awkward for sensitive customer interviews, executive 1:1s, and recruiting conversations where the bot changes the dynamic.

This is where teams sometimes prefer a tool that offers both modes. Grain ships a bot and a desktop recorder. Use the bot for transparent team capture. Use the desktop recorder for the moments when you don't want a third participant on screen.

Edge cases: external calls, customer meetings, in-person, webinars

Customer meetings: both tools handle these on Zoom, Meet, and Teams. External-call governance (who can record, default capture rules) is heavier on Fireflies admin controls than on Otter's.

In-person: Otter's mobile apps are the strongest in the category for capturing voice conversations on the go. Fireflies has a mobile app, but it is newer and less polished.

Webinars: both can capture if you can invite the bot. Neither handles complex multi-speaker webinar setups well.

Calendar and scheduling behaviors

Fireflies' calendar integration is more configurable. Auto-join rules can differ between internal and external meetings. Admins can enforce default capture policies across the workspace. Otter's calendar logic is per-user. What gets recorded depends on the individual rep's settings.

If your org wants "every customer-facing meeting gets recorded by default, every internal 1:1 doesn't" enforced at the policy level, Fireflies is closer to that out of the box.

Transcription quality, speaker identification, and language coverage

What transcription accuracy means in B2B workflows

Both tools post strong accuracy numbers when they transcribe spoken conversations on clean audio with native English speakers. The numbers stop telling the truth in four conditions: heavy regional accents, technical jargon, multiple speakers talking over each other, and bad audio.

For B2B teams, the failure modes that matter:

• Domain vocabulary. Product names, acronyms, competitor brands, technical terms. Fireflies and Otter both struggle here without a custom vocabulary feature, and neither offers one as polished as some specialist meeting transcription tools.
• Speaker identification. Both tools handle two-person calls cleanly. Both degrade past four participants. Background noise and overlapping speech still confuse both.
• Hybrid rooms. Conference room audio, with one mic for multiple people talking, is the hardest case. Neither tool excels here.

The risky failure mode isn't a blank transcript. It's a fluent, confident, wrong one. AI summaries are the most common place this shows up. The AI writes plausible-sounding language that papers over what was actually said.

Language support and global team realities

This is the most lopsided dimension between the two products.

Fireflies supports 100+ languages for transcription. Its Multi-Language Mode handles 60+ languages simultaneously in the same meeting, with word-level language detection.

Otter supports five languages: English (US), English (UK), French, Spanish, and Japanese. Otter cannot transcribe more than one language per meeting. You have to pick the language before recording.

If your team operates globally (sales conversations in Portuguese, customer success in German, leadership reviews mixing English and Mandarin), Fireflies is the only choice between these two. Otter's coverage works for English-first teams with occasional Spanish or French. Past that it doesn't fit.

Summaries, action items, and "usefulness per minute watched"

Both tools generate post-meeting recaps with action items and decisions extracted. The structural choice teams notice is how the meeting summary maps back to the recording.

Fireflies offers customizable summary templates. Decisions, key points, and action items show up as separate sections. Action items can be auto-routed to project management tools or owners. Each summary point links to the timestamped transcript.

Otter generates summaries through Otter AI Chat. Templates are template-light by default. The polish comes from Otter's meeting agents (sales agent, recruiting agent), which summarize against role-specific frameworks. Sales: objections, pain points, next steps. Recruiting: candidate strengths and concerns. The sales agent automatically drafts personalized follow-up emails and pushes insights to Salesforce or HubSpot. Full sales agent functionality requires Enterprise.

Both tools handle the basic ambiguity cases (owner unclear, decision pending) about equally. They surface the ambiguity rather than guess. Neither replaces a human reviewing critical action items.

If AI generated notes are the unit of value, both tools deliver. The question is what happens to the summary after generation, and that's where integrations matter.

Search, knowledge base, and finding answers after the meeting

Meeting library design

Fireflies' meeting library lets you filter by speaker, date, meeting type, team, and customer. Topic Trackers cluster meetings around custom topics (competitor names, pricing objections, product features) so you can see patterns across multiple meetings rather than searching meeting by meeting.

Otter's library is simpler. A chronological list of meetings with search across meeting transcripts. The new Otter AI Chat makes search feel less like a list and more like a conversation. Ask "what did the engineering team commit to last quarter?" and Otter Chat scans the meeting history to answer.

Ask-your-meetings experiences

Both tools offer Q&A across past meetings.

Fireflies' AskFred answers natural language questions about meeting content. Decisions, action items, specific topics, speaker statements. AI Credits gate AskFred usage on lower tiers (Pro plans get 20 credits per workspace).

Otter's Cross-Meeting Intelligence is the more aggressive feature. As of April 2026, Otter AI Chat acts as an MCP client that pulls live data from Gmail, Google Drive, Notion, Jira, and Salesforce. It also acts as an MCP server, so external AI apps (ChatGPT, Claude) can use Otter's meeting history as context. Ask Claude to draft a proposal using your last five sales calls. That's a category shift, not a feature.

For teams running a proof-of-concept, the things to test are speed, citation quality, and permissioning. Q&A that returns confident answers without showing the source moments is dangerous. Both tools cite back to the meeting. The depth and accuracy of meeting insights differ.

Integrations and automations that make notes operational

CRM and revenue workflows

This is where Fireflies and Otter diverge most for revenue teams.

Fireflies' HubSpot integration syncs meeting notes, transcripts, and action items. It creates contacts and leads if they don't exist. It maps summaries to deals, contacts, and companies. It auto-generates HubSpot tasks from action items. Custom deal stage support is configurable. Salesforce works through native integration plus custom field mapping.

Otter's Sales Agent takes the AI-summarizes-the-call angle. It leverages CRM data, summarizes past interactions, drafts personalized follow-up emails, and pushes pain points and objections to Salesforce or HubSpot. Full Sales Agent functionality requires Enterprise. The native CRM push is real. The sales-agent flow is the differentiator.

For Grain users syncing to HubSpot, the integration writes to discrete custom fields you can filter pipeline by, not blob notes attached to a contact. That's the structural difference between "we have a CRM integration" and "our CRM data stays clean six months in."

Slack, email, docs, and where notes go to live

Both tools push to Slack: channel summaries, owner DMs, deal rooms. Fireflies' Slack patterns are more configurable (per-channel routing, per-meeting type rules). Otter's are simpler.

Notion, Confluence, and Google Docs work for both. Fireflies through native integrations. Otter through Zapier and the new MCP connector model. Project management tools (Linear, Jira, Asana) connect through both Zapier and direct integrations on Fireflies' Business plan and above.

Zapier and webhooks: Fireflies has a deeper Zapier catalog and offers webhooks on Business+. Otter relies more on the MCP connector pattern post-April 2026.

Team collaboration features that drive team-wide usage

Sharing controls

Fireflies' sharing model supports internal and external sharing with link-level access controls. Granularity goes to the segment level: share a soundbite rather than the whole meeting. Meeting participants can leave comments and use mentions inside the meeting page.

Otter's sharing is similar. Workspaces, shared meetings, comments. External sharing depends on plan tier.

Granularity and governance

The depth difference is at the admin layer. Fireflies' Enterprise plan adds detailed governance: approval workflows, expiration links, access logging, super admin controls. Otter's enterprise tier is comparable but newer. Much of the governance posture got added in 2025 and 2026 alongside the HIPAA and SCIM rollout.

Both tools support commenting and assignments inside notes. Neither makes a clip-as-asset workflow native. That's a Grain primitive: take a meeting moment, turn it into a shareable video segment with transcript and speaker label intact, distribute via Slack, deck, or email link to the entire team.

For teams whose collaboration model is "send the moment, not the meeting", neither Fireflies nor Otter delivers it natively.

Conversation intelligence and analytics for managers

What "conversation intelligence" should deliver

The most-claimed feature in the category is also the most overhyped.

Fireflies' conversation intelligence layer surfaces talk-time, sentiment analysis, topics, and trending mentions across multiple meetings. Topic Trackers monitor custom keywords (competitors, objections, pricing) across all sales calls without a manager scanning each one. Live Assist offers in-meeting suggestions and coaching prompts.

Otter's analytics are lighter. The Sales Agent does meeting-level summarization for sales calls. Cross-meeting analytics for managers (objection trends, next-step compliance) is less developed than Fireflies'.

Neither tool has dedicated AI scorecards graded against custom rubrics. Comparison reviews note that Fireflies and Otter "lack dedicated coaching functionalities such as playbooks and scorecards." For teams that want structured coaching loops (rate each call against a MEDDICC checklist, surface the gaps, build playlists of best-rep examples), that's not what either product is.

Practical dashboards by function

Fireflies' analytics work cleanly for sales leadership: objection trends, competitor mentions, talk-ratio benchmarks. Customer success teams use the same primitives for churn signals and feature requests. Product teams pull recurring pain points by topic.

Otter's analytics are thinner. The Conversational Knowledge Engine's value isn't dashboards, it's cross-app Q&A. Different model, different audience.

Security, privacy, and compliance for enterprise buyers

SOC 2, HIPAA, and the BAA question

Both tools carry SOC 2 Type II attestations. The HIPAA story differs.

Fireflies offers HIPAA compliance on Enterprise, with Private Storage and a signed BAA. Private Storage gives Enterprise customers dedicated, isolated storage with location choice for compliance. Enterprise also includes dedicated account management.

Otter achieved HIPAA compliance in July 2025. Enterprise-only. BAA available through account managers. Both require Enterprise. Both are real.

For regulated industries (healthcare, financial services, legal), both tools clear the HIPAA bar at the Enterprise tier. Confirm DPA terms, subprocessor lists, and data residency before standardizing.

SSO, SCIM, and admin governance

Fireflies offers SSO and admin controls on Business and above. Enterprise adds SCIM and audit trails. Otter offers SSO on Business+. SCIM is Enterprise.

Both tools default to not training on customer data. Both let admins configure data retention. Confirm what "deletion" means for each data object: audio, video files, transcript, summary, structured fields. Removing the recording but leaving the summary in your CRM is not deletion.

Bot disclosure norms

US federal law and most states operate under one-party consent. California, Illinois, and most EU member states require all-party consent. Every participant must be informed before recording. Cross-border calls usually trigger the all-party standard.

A bot announcing itself in the meeting room is not a substitute for verbal disclosure. Default to "I'd like to record this for my notes, any objections?" at the start of every external call regardless of which tool you pick.

Pricing models and total cost: seats, minutes, free plans, and feature gates

Otter.ai pricing

Otter operates on a per-user-per-month model with meeting minute caps:

The 30-minute cap on the free tier and the 90-minute cap on the Pro plan is the constraint most users hit first. Many sales discoveries and customer interviews run longer than 90 minutes. The Business plan removes the cap and adds 3 simultaneous meetings. The free plan also delivers limited AI summaries compared with paid plans.

Fireflies.ai pricing

Fireflies pricing is structured similarly, with AI Credits gating the AI features:

The AI Credits model is worth understanding before purchase. Soundbites, AskFred, and AI summaries draw from the credit pool. Business and Enterprise include unlimited transcription and effectively unlimited AI summaries within a generous credit allocation. Heavy users on the Pro plan can exhaust a workspace's credits mid-month.

Hidden costs

Per-seat list prices miss most of the real cost.

• Admin time. Fireflies' configurability cuts both ways. More admin setup upfront, less drift over time. Otter is faster to deploy, slower to standardize.
• CRM cleanup. Notes pushed as activity records create data quality debt that compounds.
• Enablement production. Neither tool produces clip-based playlists natively. Teams that want them either buy a separate tool or build them by hand.
• Change management. Switching the org's meeting tool is a quarter-long project. Cost of switching is rarely on the original procurement spreadsheet.

Grain's pricing keeps free seats unlimited (viewer access for stakeholders without paying per seat) and structures paid plans around team workflows rather than per-user minute caps.

Best-fit scenarios by team type

Grain.com in your stack

A note taker that ends at "I have a transcript" solves the easy half of the problem. The harder half is what happens to the conversation after the call.

Grain treats the meeting as raw material for downstream work, not just transcripts:

• Clips as reusable assets. A 90-second customer quote becomes a Slack message, a deck slide, an exec update, or a product team prompt. The same key moment lives inside a coaching playlist and a voice-of-customer collection. Sales, CS, product, and hiring all use the same primitive.
• Playlists and stories as internal distribution. Win-story libraries for new-hire ramp. Objection-handling reels managers review on Monday. Customer-insight collections product teams cite in roadmap discussions. Exec updates pulled from real customer language instead of paraphrased narrative.
• Trackers as lightweight intelligence. Keyword and competitor alerts to Slack. When a prospect says "Salesforce" or "Gong" mid-call, the right person hears about it within minutes, without anyone scanning a transcript.

For teams whose meeting workflow is built around evidence (show the moment, not the summary), Grain's clip primitives are what make the model work. Fireflies' Soundbites are audio-only. Otter's clip story doesn't exist meaningfully. The gap is structural.

See how Grain clips work. Explore the Customer Success use case.

What is the best AI note taker for me?

The right tool depends on what your team treats as the unit of value coming out of a meeting. The key differences come down to three patterns.

If automation and a deep meeting library are the priority (pushing notes to CRM, Slack, and project management tools, with admin governance across a large org, and broad language support), Fireflies.ai is the stronger pick of the two. The integration depth and the 100+ language coverage are the real advantages.

If real-time transcription simplicity and a knowledge-engine model are the priority (fast in-meeting capture, ask-your-meetings Q&A across enterprise tools, Sales Agent automation for HubSpot or Salesforce), Otter.ai is the simpler choice. The Conversational Knowledge Engine launch in April 2026 makes it a credible enterprise option for the first time.

If shareable moments, coaching, and team-wide enablement are the priority (clips that travel between functions, playlists that compound, AI scorecards graded against your own rubric, structured CRM writes that keep pipeline data clean), Grain is the right shape. The best AI note taker is the one that fits the work after the meeting. For revenue teams, that often means conversation intelligence built around video evidence, not just transcripts. Free for teams forever, viewer seats included, with paid plans for the workflows above.

Pilot whichever tool maps to your actual workflow. Connect it to your CRM. Run it on your real meeting types. The right answer surfaces in the second week, not the first demo.

Try Grain free at grain.com/app/signup, or compare alternatives in our Otter alternatives guide and best meeting transcription software roundup.