AI Note-Taking Apps 2025: Otter, Notta, Fireflies & Others Compared

AI note-taking apps became much more than transcription tools in 2025. The leading platforms could record meetings, identify speakers, generate summaries, extract action items, answer questions about past conversations, and send information into workplace systems.

However, the apps did not offer the same experience. Some joined meetings as visible bots. Others captured audio directly from the user’s device. Some focused on multilingual transcription, while others were designed around sales coaching, CRM automation, or analysis across many meetings.

The best choice therefore depended on the user’s actual workflow. A student recording lectures had different needs from a sales team processing hundreds of customer calls. A researcher might prioritize accurate exports and language support, while a manager might care more about searchable meeting history and team analytics.

This comparison examines Otter.ai, Notta, Fireflies.ai, Fathom, tl;dv, Avoma, Granola, and Read AI as they competed during 2025. Plans and usage limits changed frequently, so exact prices should always be checked separately.

What Is an AI Note-Taking App?

An AI note-taking app converts spoken conversation into a structured digital record. The basic output is usually a transcript, but many platforms also create summaries, decisions, tasks, chapters, highlights, and follow-up messages.

Some apps operate mainly as transcription services. Others act as meeting assistants that join calls automatically. More advanced platforms add conversation intelligence, coaching, CRM updates, and analysis across an entire meeting library.

Not every user needs all of these functions. A large feature list may create unnecessary cost and complexity when the real requirement is simply a searchable transcript and a reliable summary.

How the Apps Were Compared

A useful comparison should go beyond vendor accuracy claims. The same app may perform well in a quiet one-to-one interview but struggle with technical vocabulary, background noise, or several people speaking at once.

The most important evaluation criteria include:

• Transcription accuracy
• Speaker identification
• Summary quality
• Action-item detection
• Language support
• Search and AI chat
• Meeting-platform compatibility
• Export and integration options
• Privacy and administrative controls
• Free-plan and paid-plan limitations

The complete workflow matters. A slightly imperfect transcript may still be useful if the summary is accurate and easy to edit. A highly accurate transcript may create less value if it is difficult to search, share, or move into another system.

Meeting Bots and Bot-Free Capture

One of the biggest differences between AI notetakers is how they capture a meeting.

A bot-based service joins Zoom, Google Meet, or Microsoft Teams as another participant. This makes recording visible and allows the app to join scheduled calls automatically. However, some clients dislike seeing an extra participant, and meeting hosts may block external bots.

Bot-free tools capture audio through the user’s computer or mobile device. They create a more natural meeting experience and can work across platforms that do not support automated bots.

Bot-free capture does not remove the need for consent. The person using the tool remains responsible for informing participants and following organizational rules and local recording laws.

Otter.ai

Otter remained one of the most recognizable general-purpose AI meeting tools in 2025. Its central strengths included live transcription, collaborative notes, automated summaries, action items, and an AI assistant that could answer questions based on meeting content.

It supported common workplace platforms, including Zoom, Google Meet, and Microsoft Teams. Users could review a live transcript during a call, highlight key information, edit speaker names, and share the final record with colleagues.

Otter was especially useful for people who wanted a familiar interface and real-time access to notes. Its collaborative workflow made it suitable for internal meetings, interviews, classes, and team discussions.

The main limitation was plan-based usage. Meeting length, monthly transcription, file imports, administrative controls, and advanced integrations depended on the selected tier.

Best for: general meeting transcription and collaborative live notes.

Notta

Notta stood out for multilingual work. It supported live transcription, uploaded recordings, meeting summaries, action plans, speaker labels, and translation-related workflows.

This made it attractive for international teams, multilingual interviews, webinars, lectures, and users who regularly worked with audio files rather than only live meetings.

Notta could join calls through a meeting bot and also process uploaded content. Its broader language focus gave it an advantage over products designed mainly around English-language business meetings.

Users still needed to test the specific languages, accents, and terminology relevant to their work. A long language list does not guarantee identical accuracy across every language.

Free and lower-priced plans also placed limits on minutes, recording length, uploads, exports, or advanced AI functions.

Best for: multilingual meetings, interviews, and uploaded recordings.

Fireflies.ai

Fireflies developed into a workflow-oriented meeting platform rather than a simple transcription tool. It could record meetings, generate summaries, identify action items, create searchable conversation records, and connect notes with other business tools.

Its integrations were a major strength. Teams could send information into collaboration platforms, task-management systems, and customer relationship management software.

Fireflies also introduced real-time meeting notes and transcripts during 2025. Participants could view live notes, speaker-labeled transcripts, bookmarks, and action items while a meeting was still taking place.

The platform was particularly useful for organizations with many recurring calls and a need to reuse meeting information across several systems.

Its expanding feature set could feel excessive for an individual who wanted only a transcript. Users also needed to examine storage, AI-credit, integration, and administrative limits carefully.

Best for: workflow automation and broad business integrations.

Fathom

Fathom was one of the strongest options for individuals looking for a generous free experience in 2025. Its official documentation stated that individual users could keep unlimited recordings and storage on the free version.

The app recorded supported video meetings, produced transcripts and summaries, and allowed users to create or share highlighted moments. Paid plans expanded access to advanced summaries, action items, follow-up content, team administration, and CRM-related features.

Fathom was well suited to consultants, recruiters, founders, and customer-facing professionals who participated in many calls but did not want to pay for every recorded minute.

Users still needed to examine which AI summaries and advanced features were included in each plan. A service may offer unlimited recording while limiting higher-value AI outputs separately.

Best for: individual professionals seeking a strong free recording plan.

tl;dv

tl;dv focused on recording, transcription, summaries, clips, and analysis across multiple meetings. It worked with Zoom, Google Meet, and Microsoft Teams and could join scheduled meetings as a visible participant.

Its strongest use case was not simply documenting one call. Teams could search recurring conversations, identify repeated themes, and review customer or research insights across several meetings.

The platform also emphasized multilingual transcription and integrations with collaboration, project-management, and CRM systems.

This made tl;dv useful for customer research, sales, recruitment, and distributed teams that needed to compare information across calls.

Advanced reports, automation, CRM workflows, and multi-meeting AI functions could depend on paid plans or usage allowances.

Best for: multilingual teams and analysis across repeated meetings.

Avoma

Avoma was broader and more specialized than a basic AI notetaker. It combined meeting transcription and notes with scheduling, CRM synchronization, sales coaching, conversation intelligence, and revenue-related analysis.

During 2025, Avoma continued expanding features such as instant notes, action items, automated CRM updates, risk alerts, coaching tools, and pipeline intelligence.

These functions were valuable for sales and customer-success teams. A representative could finish a call with notes, tasks, and customer information already prepared for the CRM.

The disadvantage was complexity. Students, researchers, and occasional meeting users were unlikely to benefit from revenue intelligence, sales methodologies, call scoring, or pipeline analysis.

Avoma also used recorder-seat and add-on structures that required careful cost calculation for larger teams.

Best for: sales, customer success, and revenue operations.

Granola

Granola offered one of the most distinctive workflows in the group. Instead of sending a visible bot into the meeting, it captured audio through the user’s device and combined the transcript with notes written by the user.

The result felt more like an AI-enhanced notebook than a fully automated meeting recorder. Users could write rough notes during a call and allow Granola to organize, expand, and structure them afterward.

This approach was attractive to founders, product managers, researchers, and professionals who wanted to remain actively involved in note-taking without producing a complete record manually.

Granola expanded its integrations and relationship-oriented organization features during 2025, including connections with automation and CRM tools.

Because capture depended on the user’s device, the user needed to attend the meeting and manage recording consent directly.

Best for: bot-free, human-guided AI notes.

Read AI

Read AI combined meeting transcription and summaries with analytics, coaching, search, and reports about communication patterns.

It could identify action items, create meeting reports, offer playback and highlights, and help users search previous information through Ask Read. During 2025, the platform expanded its context search, folders, mobile access, and broader productivity features.

Read AI was useful for managers and teams interested in both the content of meetings and the way meetings were conducted.

However, participation scores, talk-time measurements, and coaching metrics could feel intrusive when introduced without clear explanation. Organizations needed policies describing how analytics would be used and who could see them.

Best for: meeting analytics, coaching, and searchable organizational context.

Side-by-Side Comparison

Which App Was Best for Students?

Students usually needed affordability, searchable transcripts, uploaded-file support, clear exports, and easy organization. Otter and Notta were practical candidates, particularly when live transcription or language support mattered.

Fathom could be attractive for supported online classes, but its workflow was more closely associated with meetings than traditional lecture recording.

Students should never assume they are allowed to record a class. Permission may be required from the teacher, institution, and other participants.

Which App Was Best for Researchers and Journalists?

Researchers and journalists needed timestamps, speaker labels, exports, uploaded recordings, and careful deletion controls.

Notta was a strong candidate for multilingual interviews. Otter offered convenient live transcripts, while Granola provided a less visible bot-free experience.

AI transcripts should not be treated as verified quotations. Names, numbers, specialized terms, and direct quotes must be checked against the recording before publication.

Which App Was Best for Remote Teams?

Fireflies, tl;dv, Otter, and Read AI were strong options for remote teams. They provided shared archives, summaries, task extraction, and integrations with common workplace tools.

The best choice depended on what happened after the meeting. Fireflies emphasized automation, tl;dv emphasized recurring insights, Otter emphasized live collaboration, and Read AI emphasized analytics and broader search.

Which App Was Best for Sales Teams?

Avoma was the most specialized option for revenue teams because it connected meeting records with coaching, CRM data, scheduling, and pipeline workflows.

Fireflies and tl;dv were more flexible alternatives for teams that wanted CRM integration without adopting a complete revenue-intelligence platform. Fathom was attractive to individual sales professionals and smaller teams seeking simple capture and follow-up support.

Privacy and Consent

AI notetakers may process customer information, voices, names, financial discussions, internal plans, and other sensitive material.

Organizations should review data retention, deletion controls, administrator access, encryption, AI training policies, regional storage options, and available compliance documentation.

A security certification does not automatically make an app appropriate for every confidential meeting. The organization must still decide which conversations can be recorded and how long the records should remain available.

Participants should be informed clearly. A visible meeting bot may help signal recording, but it should not replace direct notice when consent is required.

Common Selection Mistakes

One mistake is choosing only by claimed transcription accuracy. Real value also depends on editing time, summary quality, search, integrations, exports, and privacy.

Another mistake is comparing a free plan from one service with a paid plan from another. “Unlimited” may apply only to recordings while summaries, storage, AI questions, or integrations remain limited.

Teams may also pay for advanced features they never use. Sales coaching has little value for a student, while multilingual transcription may be unnecessary for an English-only internal team.

Finally, vendor demonstrations usually use clean audio. Shortlisted apps should be tested on real microphones, accents, vocabulary, platforms, and meeting types.

A Practical Selection Process

1. Define the meetings that need to be recorded.
2. Choose between visible-bot and bot-free capture.
3. List the required languages.
4. Decide whether the output must include transcripts, summaries, tasks, or coaching.
5. Review consent, retention, and deletion requirements.
6. Calculate costs for seats, storage, credits, and integrations.
7. Test at least two apps on the same meetings.
8. Measure how much editing each result requires.
9. Confirm that exports and integrations fit the existing workflow.
10. Review actual usage after the first month.

Final Verdict

There was no universal winner among AI note-taking apps in 2025.

Otter was a balanced choice for live collaborative notes. Notta was better suited to multilingual work. Fireflies offered strong automation and integrations. Fathom provided an attractive free experience for individual professionals.

tl;dv was useful for analysis across many meetings. Avoma delivered the deepest sales and revenue workflow. Granola provided a distinctive bot-free notebook, while Read AI focused on meeting analytics and organizational context.

The right tool was not necessarily the one with the longest feature list. It was the app that produced reliable notes, required little correction, respected privacy requirements, and moved information into the system where the next stage of work took place.

Editorial note: This article describes the 2025 product landscape. Pricing, limits, integrations, language support, and free-plan conditions may have changed since that period.