Some of the best AI meeting assistants are Lindy for post-meeting follow-ups, Otter for live transcription accuracy, and Avoma for sales coaching. Each tool solves a different problem, but they all help teams capture and act on information faster.
Without meeting assistants, teams lose follow-up details, miss CRM updates, and waste time rewriting notes manually.
Here are the 10 best AI meeting assistants that help solve these problems. Discover how each tool transcribes meetings and extracts key insights so you can pick the right one for your team.
I started off with 20 AI meeting assistants and boiled my list down to 10 by testing the following criteria:
I found 10 tools that noted key points from messy conversations and could send info to CRMs and calendars so the whole team could stay informed. The meeting assistants that failed added more work or didn’t connect with other apps.

What it does: Lindy handles follow-ups after meetings by updating your CRM, drafting recap emails, and creating next-step tasks.
Who it's for: Teams running high call volume who need scheduled meetings, summaries, and follow-ups completed before the next call starts.
I tested Lindy on a mock 40-minute sales discovery call. The “lead” gave me 3 action items and a pricing follow-up during the meeting. All I needed to do was text Lindy and tell it to capture each action item in the summary and send it to a Google Doc. The summary read like it was written by someone who actually attended the meeting and took precise notes.
It then sent a Slack notification to members of the finance team to ask for guidance about the lead’s pricing question. The team immediately understood the lead’s pricing question and provided an answer after a little internal discussion. This means I was prepared for the follow-up call.
Lindy also texted me 10 minutes before the follow-up meeting with a recap of the action items we agreed on during the previous call. It also showed how I had completed each task and gave me a clear way to present that progress to the lead.
I also tested Lindy across a sample daily meeting schedule with changing agenda items. Lindy assigned tasks with reasonable accuracy and updated each item in every team member’s Google Calendar.
This keeps your team aligned without constant recap meetings or repeated explanations. Lindy helps you avoid endless emailing and wasting time repeating yourself just to get your team up to speed. You can instead focus on the reason for the meeting instead of repeating updates.
The only issue I had with Lindy was that I needed to be specific about what I wanted it to do. For instance, if I told it to summarize a sales call, it would sometimes leave out important objections or next steps. I needed to tell it to capture objections, pricing concerns, action items, and follow-up commitments to produce stronger summaries.

“I sent about 40 outreaches and got one connected. Definitely saved hours and hours of work. It would have taken forever to do cold emails to 40 leads. And I probably got it done in 1-2 hrs.” - Reddit user

“For AI, it is expensive for what it does. Did lag and overall just not a great experience. The automation [is] better than doing myself, but hopefully they fix the credit system because its limited.” - Sally J., Trustpilot
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What it does: Otter transcribes every spoken word during a meeting in real time.
Who it's for: Teams with several back-to-back calls who need a searchable record without manual effort.
I tested Otter on a 60-minute internal planning call with 6 attendees. The tool could identify speakers through most of the session, but had 4 errors matching the speakers in the back half of the call.
The next test looked at the live transcript feature during a client call. This feature generated what everyone said in near real time. I could reference the client’s exact wording to guide follow-up questions and avoid missing important details during the conversation.
But if you’re running calls longer than 90 minutes, you’ll need to upgrade to the Business Plan, which is more than double the price of the Pro Plan. Since Otter charges per user pricing, costs could add up if you have a growing sales team.

“It did a very good job of transcribing a very long meeting I trialed. Output was clear and unambiguous.” - Adrian Rath, Trustpilot

“...in meetings with multiple people, Otter can struggle to distinguish between voices. It might mislabel speakers or treat one person as two, which makes reviewing the transcript confusing sometimes.” - Hawa L., G2

What it does: Avoma handles call review by scoring every rep conversation and surfacing coaching gaps automatically.
Who it's for: Sales managers running weekly pipeline reviews who need call data without listening to recordings.
I tested Avoma's scorecard feature across 5 sample discovery calls that I had recorded earlier. The tool scored talk ratio, question frequency, and topic coverage against a custom rubric without manual input. That level of call breakdown would take a manager 30 minutes per call to replicate manually.
Then, I examined the deal research feature for a sales pipeline review. Avoma showed me the potential clients that had gone dark based on call activity. It flagged 3 new opportunities with those leads to help my team revisit.
But teams without a dedicated sales manager or structured coaching program will find Avoma's depth more overhead than payoff. To properly use the tool, you’ll need a dedicated sales manager and training process.

“Avoma is most helpful for capturing meeting notes, summaries, and action items automatically, which saves time and reduces the chance of missing important details.” - Miles H., G2

“One thing I don't like is that sometimes the automatic notes are not perfectly accurate. Most of the time, they are good, but occasionally a word or sentence may not be captured exactly right, so I still need to review them quickly. Another small issue is that it takes a little time to get used to all the features.” - Sanket P., G2

What it does: Read AI helps your sales teams with post-meeting review by scoring participation, attention, and sentiment.
Who it’s for: Sales leaders who need behavioral data for both reps and leads across calls.
During testing, I used Read AI's meeting score feature across 10 sample sales calls with 6 regular attendees. The engagement scores flagged two participants as consistently low-attention, which would help managers find ways to improve these reps’ performance.
I also tested the cross-platform search against a sample client’s contract with activity spread across Zoom calls, internal Slack threads, and email. Read AI pulled context from all 3 sources and returned a coherent summary. These features would solve the problem of sifting through several sources and trying to pinpoint bottlenecks or client concerns.
Teams that only need transcripts and action items may find Read AI too feature-heavy. Users who rarely use the cross-channel or scoring features would pay for functions that they don’t use.

“I use Read AI to record our office meetings and webinars I can't attend, and I appreciate the transcription and note summaries it provides. I find it solves the problem of attending multiple meetings at once, and the notes are amazing.” - Mary K., G2

“Sometimes it doesn't join meetings even though you invited it, and while adding it to an already ongoing meeting, sometimes I get confused as to whether it is recording or not.” - Harsha M., G2

What it does: Krisp improves call clarity by removing background noise and applying real-time accent conversion.
Who it's for: BPOs and offshore contact centers running hundreds of daily calls with noise and accent variables.
I tested Krisp's noise cancellation and accent conversion on a simulated offshore support call with heavy background noise. The tool reduced agent-side accent and background noise, without a lag. That combination alone removes two of the most common reasons call center CSAT scores drop.
I then tested the Agent Assist feature during 5 mock troubleshooting calls. Krisp offered several suggestions for multiple escalation paths based on what each customer said. This would help improve handle time for customer service reps by reducing the time spent pausing and searching through a knowledge base.
The trade-off is that Krisp is more suited to teams with over 40 agents. Krisp’s Core plan only provides 1 hour daily of accent conversion, which limits use if you handle several service calls every day.

“I really like Krisp's noise reduction feature. I can have somebody clapping next to me, and it won't be heard by the microphone; only my voice will be. Even if a dog is barking in the front of my house or if I'm typing something, those sounds won't be picked up.” - Diego F., G2

“The recording every time I make or receive a new call can be a little annoying sometimes; it often causes delay while on the phone.” - Rebecca C., Capterra

What it does: Fireflies replaces scattered notes and manual CRM entry by indexing meeting calls into a searchable team archive.
Who it's for: Teams sharing meeting context across departments who need to find past decisions without asking anyone.
I tested Fireflies across 8 mock client calls on a 5-person team with shared Notebook access. Every transcript landed in the shared workspace automatically, tagged by speaker and timestamped without manual input. This feature could help teams organize follow-ups and action items by having a direct record of what decision makers say.
Then, I ran tests with the AskFred feature against a file of mock sales calls and filtered for objections. It returned a summary across multiple meetings, which helped spotlight different reasons for rejections. I could see how this could help a sales team learn how to fix reasons for rejection so they can close more deals.
However, Fireflies struggled with a solo freelance mock task that had only one recurring meeting type and no shared team context. The Notebook structure, channel organization, and collaboration features added extra steps without giving a single user much value. Fireflies is built for teams, and solo users feel that overhead almost immediately.

“The automated meeting summaries and action-item extraction are absolutely fantastic. They eliminate the need for anyone to take manual notes during client calls or internal team syncs, which means everyone can stay fully present in the conversation.” - Denis M., G2

“2 big pain points: 1) their HubSpot integration is unreliable. Tasks often don't get assigned to the right deal/companies, which creates a huge pain in the back. 2) their summary emails are full of marketing rubbish.” - User on G2

What it does: Fathom records, transcribes, and summarizes calls.
Who it's for: Individual contributors with 10+ meetings weekly who want accurate notes without paying anything.
I tested Fathom across a full week of sample client calls on Google Meet. The system sent summaries within 60 seconds of each call ending. Fathom formatted each one with action items already separated from the discussion context. This system would help sales reps send follow-ups right after calls ended.
During testing, I tried Fathom's highlight clipping on a 75-minute mock strategy call. The tool tagged moments mid-call. In a single keystroke, I could create a usable clip library without any post-call editing. That could help teams prepare for follow-up conversations in minutes.
Fathom mainly works around bot-joined video calls. This is a trade-off if your team relies on in-person meetings or phone calls. To capture those conversations, you’ll need to route them through supported video platforms or separate recordings.

“The app joins meetings so fast, and it’s very easy to use, so you don’t need to be an expert. If you ever get lost, you can just copy the link, click “add link here,” and paste it to join. Once the meeting ends, it’s really easy to view everything on one page and share it.” - Amr E., G2

“There are some bugs in terms of sharing recordings and granting access. For myself, it's not something I usually care about, but if you're working with a team, be aware that it takes a learning curve.” - Rachel R., Capterra

What it does: tl;dv creates clips, timestamps key moments, and shares highlights from calls.
Who it's for: Product and research teams sending call evidence to people who will never watch a full recording.
I tested tl;dv's clip-sharing feature on a 60-minute mock call. Creating timestamped clips from the transcript took under two minutes without touching the video timeline. For teams that present user evidence to stakeholders, the speed changes how often insights actually get shared.
The multi-meeting AI report feature worked across eight customer calls from a single sprint cycle. tl;dv discovered recurring themes and grouped them by topic without requiring any manual tagging. That output could help teams speed up sales cycles.
Teams expecting tl;dv to work like a full CRM should know most automation runs through integrations. After setting up tools like Zapier, transcripts and summaries can create tasks, send follow-ups, and sync data automatically, but it’s not fully plug-and-play.

“The automatic recordings, transcripts, and highlights make it easy to stay aligned across teams and ensure nothing gets lost after calls. I especially appreciate how simple it is to share specific snippets with colleagues.” - Dennis H., G2

“...what I dislike about tl;dv is that the pricing feels a bit steep, making it a rather expensive investment for what it offers. Additionally, while the AI summaries are top-notch, the actual transcripts definitely need work; I’d love to see more accurate word-for-word transcriptions to match the high quality of the rest of the tool.” - CEO., G2

What it does: Fellow organizes meetings, captures action items, and tracks follow-through between sessions automatically.
Who it's for: Teams running recurring 1-on-1s and team syncs.
I tested Fellow's agenda and action items across a 4-week meeting dataset of mock team syncs. Action items from each meeting carried forward automatically into the following session's agenda without any manual input. That single behavior would help cut meeting time down and allow teams to focus on what really matters.
The AI note-taker generated a summary on a mock 45-minute 1-on-1. The summary mapped directly to the agenda sections already in the note. The output read like it was catered to help that specific employee improve. It didn’t seem like a stale repetition of how to meet company best practices.
But if your teams rarely pre-build agendas or run ad-hoc calls without structure, you might find Fellow's meeting-first design adds overhead without payoff. The AI output needs a premade agenda. Without one, the summaries are competent but unremarkable.

“Fellow makes it easy to create structured, collaborative meetings by providing clear agendas, shared notes, action items and follow-ups with reminders. Its AI assistance helps with note-making, summarizing key points and transcribing discussions, allowing participants to stay fully engaged in the meeting.” - Swapnil S., G2

“The application has a limited trial period and is expensive compared to others for the same offerings. Also, the transcription is not that good.” - Anddy R., G2

What it does: MeetGeek records, transcribes, summarizes, and routes meeting output to connected tools without manual steps.
Who it's for: Ops and customer-facing teams running high call volume who need documentation handled without touching it.
I tested MeetGeek across several files of mock customer call data that connected to Slack and HubSpot. Summaries consistently appeared in the right Slack channels and CRM records within minutes, with meeting types categorized accurately. For teams that struggle with documentation, the automation required very little manual oversight after setup.
The analytics dashboard gave me data on a sample set of 20 team calls. MeetGeek pulled up talk-time distribution, topic frequency, and sentiment trends with very little manual tagging or setup. Those features are usually tied to more expensive conversation intelligence platforms.
However, teams with low meeting volume may find MeetGeek’s automation depth excessive. The platform works best with consistent, repeatable meeting types because irregular calls do not generate enough data for meaningful analytics.

“The best feature about MeetGeek is the insights it brings out after a meeting, not only to learn and continue with best practices, but to show any way to increase and get better results when communicating and having more sales closed.” - Adrian P., G2

“We paid up to access features we needed, but they didn't work without speaking with customer service/tech team. (I'm still waiting for a key feature to work correctly after 2 weeks, for example) Plan tiers also don't really help small businesses who can't afford some things, but need the extra help.” - Consulting Professional, G2
The right AI meeting assistant depends on what your team needs after calls end. Here’s how to pick the right tool for your needs:
Want an AI assistant you can text instead of a platform you constantly configure. Lindy joins meetings and handles follow-ups, CRM updates, and recap emails when prompted.
Take back-to-back calls and need every spoken word captured and searchable in real time.
Manage a sales team and coach on call data, review rep performance weekly, and need scored call records and pipeline risk flags.
Host meetings across Zoom, Slack, and email, and identify participation gaps found from all three sources together.
Have customer service agents who take hundreds of daily calls in noisy or multilingual environments and need audio quality fixed.
Need every call indexed into a shared archive so anyone can search past decisions without asking a teammate.
Attend 10 or more meetings weekly and need structured notes with action items ready at no cost.
Share highlights with people who weren't on the call.
Manage 1-on-1s where unresolved action items need to carry forward automatically between sessions.
Have a team that handles repeatable call types and needs summaries and CRM updates routed automatically after every call.
Host most meetings in person, handle legally privileged or regulated conversations, or run very few recurring meetings. Most AI meeting assistants work best with recorded virtual calls and repeatable workflows. If your conversations involve confidential legal, healthcare, or financial discussions, you may need stricter review policies before using AI meeting assistants.
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Most AI meeting assistants only record and summarize meetings. Lindy also handles the follow-up work after calls end. Just text Lindy what you need, and it updates your tools, drafts, follow-ups, and organizes next steps.
Here’s why more businesses choose Lindy as their AI meeting assistant:
The best AI meeting assistant depends on what tasks you need to handle. Otter is excellent for live transcription accuracy. Fathom is the top free option. Lindy is strongest for post-meeting follow-ups, CRM updates, and recap drafts. Choose the tool based on what your team needs after meetings, such as follow-ups, coaching, CRM updates, or searchable transcripts.
Yes, AI meeting assistants are accurate for meeting notes and transcripts in most standard conditions. But strong accents and technical jargon can reduce reliability. Tools like Krisp and Fireflies performed well in testing. Review AI-generated summaries before sending them to clients to avoid mistakes or missing context.
The AI meeting assistant best suited for sales calls and customer meetings is Lindy. It syncs action items, pricing objections, and follow-up drafts directly into your CRM. Avoma is the stronger choice if sales coaching and rep performance scoring matter, reducing manager review time per call.
The best AI meeting assistant for Microsoft Teams depends on your workflow needs. Fellow integrates natively via Microsoft AppSource without requiring a bot to join calls. Lindy joins Teams calls, captures structured notes, and handles CRM updates and follow-up drafts after each call ends.

Lindy saves you two hours a day by proactively managing your inbox, meetings, and calendar, so you can focus on what actually matters.
