September 23, 2024
The post-ChatGPT world is well and truly here. AI-driven meeting summarizer tools are abundant, and we have more choice than ever to summarize any kind of text. All to make better decisions quickly, no matter what your source of text: hundreds of call transcripts, extensive research papers, expert articles and so much more. But how do you choose the best AI summarizer based on your use case?
Before I get into the quickly evolving world of text-based AI, let’s understand the basics.
AI-driven meeting summarization tools help us mortal humans digest vast amounts of information and present it in a concise, easy-to-consume format.
There are many business reasons to use AI summarizers, and I’ll get into those in just a bit. But for now, let’s imagine Sarah, a busy SaaS entrepreneur who has hundreds of calls and meetings as she builds her team and business from the ground up.
Every day, Sarah is inundated with tens of call transcripts, some with her prospective employees and many with business prospects and partners. A hundred emails, at the minimum. She must also keep up with the trends and news in her industry and community. There’s always something going on and she can’t help but wonder if she’s missing some piece of important information she needs in life or business.
A day in the life of Sarah, without the best AI summarizer ;)
Sarah loves her work, sure. But likes having time to herself even more. Where’s the time for that, though? Well, she can and hopefully does, find that time with AI summarizers :)
AI meeting summarizer tools are innovative applications that condense large volumes of text into concise, easily digestible summaries. With AI superpowers, these tools have an uncanny ability to identify and extract the most crucial points, presenting them in a clear and structured format, reshaping the way people consume information, making the process far more efficient and enjoyable.
In a world where the importance of timely and accurate information keeps growing, AI summarizer tools are indispensable to make better decisions, know and understand more, and achieve a semblance of work life balance!
Full disclosure. Text summarization is pretty close to my heart. I started out working in natural language processing during a winter internship at Stride.ai, where I worked on text summarization models for news. That project helped me go deep into the topic, and I ended up working on summarization in a variety of projects after that in school, work, and eventually in my own startup, Sybill.
In this guide, I dive into the different kinds of summarization, the top use cases for it, and the most popular AI summarizer tools for each use case. The meeting summarizing space is evolving very quickly, since there are new AI tools developed and deployed every single day, and a new summarizer every week that’s based on some alteration in a popular large language model (LLM). I hope you’ll get a lot out of this guide as you make your own choices.
Before we dive into the best AI summarization tools, let’s look into what we exactly mean when we talk of a summary. There are two technical ways in which a summary is created:
Extractive summarization selects key sentences or phrases from the original text to form a summary. While it preserves the text's original wording, the summaries can sometimes lack fluidity or omit crucial context.
When you pick out the most important or representative quotes from a graduation speech, it’s a form of extractive summarization.
Abstractive summarization rephrases and restructures the original text to craft a summary. This method produces smoother summaries that encapsulate the text's essence, but it might occasionally introduce errors or stray from the original content.
When you go home after work and tell your partner or friend about how your day was, that's an abstractive summary.
Hybrid summarization combines elements of both extractive and abstractive summarization. It first identifies the key sentences or phrases (extractive approach) and then rephrases or restructures them (abstractive approach) to create a coherent and concise summary. This method aims to leverage the strengths of both techniques to produce more accurate and fluid summaries.
Imagine you are summarizing a detailed project report. You select the most important sections and key points (extractive) and then rewrite them in a cohesive narrative that highlights the project's progress and outcomes (abstractive).
ChatGPT, powered by OpenAI, is a popular AI summarizer for general-purpose text. It excels at generating coherent and concise summaries while maintaining the overall meaning of the source text. You can also tune the length, the tone, and the focus of the summary by cleverly prompting it and stating your intent. There’s little surprise that this magic summarizer, available for less than a few McDonald’s meals, has over 100 million users and a base that keeps growing exponentially every day!
But there’s a catch. ChatGPT may generate summaries that deviate from the original content or introduce inaccuracies. It might also miss important details from summaries. It’s not quite equipped to understand what a domain-specific important detail is. For instance, a prospect might mention in a sales call that they use Salesforce as their CRM system, but if that’s the only sentence in a 45-minute call that references this fact, ChatGPT may fail to pick it up while summarizing the call, since it doesn’t know that could be an important detail for the salesperson.
Pros:
Cons:
Free plan: $0 per user per month
Plus plan: $20 per user per month
Overall, while ChatGPT is a powerful tool for general summarization tasks, it may not be the best choice for highly specialized or domain-specific needs without careful prompting and adjustments.
QuillBot is a versatile AI summarizer that works well for general-purpose text summarization. It offers multiple modes, including standard, creative, and formal, to cater to various content types. However, it may not always provide the most accurate summaries, especially when dealing with complex or niche topics.
Source: Quillbot website
PS: QuillBot has also nailed the SEO game for AI summarizers, and I tend to be a little skeptical of the tools that do because their superior SEO position gives them a chance over the long term not to be the innovation leader and still get the required demand. However, I recommend you try it out for yourself and figure out if it’s a good fit for your use case. QuillBot recently wrote about how it can work together with ChatGPT. I personally don’t find the arguments convincing enough - whatever it says that QuillBot can do (summarize, paraphrase, etc.) on top of ChatGPT output is something ChatGPT can also do by itself. However, plagiarism detection and citations might be interesting topics to look into if you’re considering QuillBot.
QuillBot recently wrote about how it can work together with ChatGPT. I personally don’t find the arguments convincing enough - whatever it says that QuillBot can do (summarize, paraphrase, etc.) on top of ChatGPT output is something ChatGPT can also do by itself. However, plagiarism detection and citations might be interesting topics to look into, if you’re considering QuillBot.
Pros:
Cons:
Free: $0 per user per month
Premium: $9.95 per user per month
Overall, QuillBot is a solid choice for general-purpose summarization and offers some unique features, but it may not be the best option for specialized or highly complex texts.
Otter.ai has established itself as one of the best end-user-facing transcription tools out there. It has a low word error rate, a decent way of matching statements to speakers, and doesn’t generally crash. But is Otter a good bet for call summaries?
Depends on how good you want your AI summarizer to be in the context of conversations.
For example, the above is a summary of a call that I had, discussing a content writer position in my startup, Sybill. As you can see, it’s not really a summary.
Otter produces an outline of the conversation, sort of like creating chapters. And the chapters are decent, but they don’t add up to a summary at all. They are pointers to specific timestamps in the transcript.
If that’s what you want, and you’re okay listening to the call transcript later on, Otter might work for you. If you really want a summary that’s both accurate and covers the gist of the call without having you watch or listen to the call, then Otter’s summaries fall short.
Pros:
Cons:
Basic plan: Free
Pro plan: $8.33 per user per month
Business plan: $20 per user per month
Enterprise plan: Custom
Overall, Otter is a robust tool for transcription with real-time capabilities and good speaker identification. However, it may fall short in providing comprehensive and accurate summaries of conversations.
Fireflies.ai is another popular meeting transcription software with a slick UI. It excels in the number of integrations it has with meeting providers, and the number of supported languages. Let’s look at the summaries now:
As you can see, the summary includes a few key pointers from the meeting. It’s a pretty good starting point for summarizing general-purpose meetings. You can read more about their summarization and how they compare in their own article.
However, Fireflies suffers the same issue that AI summarizers at the heart of meeting providers like MS Teams suffer: their summaries are general purpose. They include key pointers like tasks, decisions and next steps, but don’t capture domain-specific information.
For example, a user research-focused summarizer would have a section that captures feature requests. A sales-focused summarizer would have a section that captures the prospect’s areas of interest. A customer support-focused summarizer would have a section that captures customer pain points with their usage of the product or service.
Pros:
Cons:
Free: $0 per seat per month
Pro: $10 per seat per month
Business: $19 per seat per month
Enterprise: $39 per seat per month
Overall, Fireflies is a strong contender in the meeting transcription space, offering extensive integrations and multilingual support. However, its general-purpose summaries may not meet the specific needs of specialized domains, making it less effective for certain use cases.
You get the drill. And this brings us to…
I am one of the founders, so I could be biased. G2 users, on the other hand…
Let’s see how Sybill does against the criteria that I highlighted above.
Sybill has a lot of context about conversation participants (their role, their LinkedIn profile, call metadata, and more), and a pretty good level of conversation and company context as well.
It captures all the key points of interest, pain points, and points of hesitation or objections from calls in neat sections. The summaries come right into your email and Slack, as well as get pushed into your CRM systems automatically tagged to the right opportunity, company, and contact.
Sybill is also the only sales summarization tool in the market that captures and synthesizes insights from video data. It captures participant engagement and excitement levels by quantifying their non-verbal reactions throughout the call, which provides key insights into all buyers’ interest points and areas where they didn’t really care.
Behavior AI + Generative AI = best-in-class call summaries.
Sybill also supports the customization of call summaries for various RevOps teams like customer success, sales, and product.
Sybill was the first sales intelligence tool to introduce structured call summaries and will continue to maintain the innovator’s lead. We’re building Sybill to be the all-in-one personal assistant for sales professionals.
Oh, and before I forget. Sybill also crafts an automated follow-up email from the summaries that it generates, so you can send a follow-up with just a click. It’s shown to save 45-60 mins per day in follow-ups and note-taking for an average SaaS sales rep.
The only con? Starting at $59, it could be a little pricey for small businesses but that pricing comes for the best-in-class 95% accuracy that Sybill offers in return.
Pros:
Cons:
Starter: $59 per user per month
Mind Reader: $65 per user per month
Enterprise: Custom pricing
Overall, Sybill stands out as a powerful AI meeting summarizer, particularly for sales teams, due to its high contextual understanding, video insights, and automation capabilities. While it may be a bit pricey for some, the advanced features and time savings it offers make it a valuable investment for many businesses.
Avoma summarizes sales calls neatly into various sections as well. It’s a meeting intelligence platform and aims to assist sellers before, during, and after each meeting. It fairs pretty well on having participant context, and capturing key takeaways from meetings.
Avoma integrates pretty well with CRM systems (they don’t mention a Slack integration on their website) as well and allows category customization in the summaries.
Avoma doesn’t capture participant reactions during the call, and therefore its summaries only focus on the most important takeaways from the transcript, rather than focusing on the trifecta of the transcript, audio tonality, and video.
Avoma also doesn’t create follow-up emails from summaries or surface any recommended next steps based on deal context.
Overall, it’s a good call recording and summarization tool. However, the lack of capabilities in taking advantage of the summary for actionable next steps like email creation, and the unavailability of insights based on buyer engagement and excitement levels makes its price tag seem a little steep.
Pros:
Cons:
Basic: $0 per user per month
Starter: $19 per user per month
Plus: $49 per user per month
Business: $79 per user per month
Enterprise: $129 per user per month
Overall, Avoma is a solid choice for call recording and meeting summarization, especially for teams needing structured and customizable summaries. However, its lack of multimodal capabilities and actionable insights may be a drawback for some users, particularly given its price.
Momentum recently came up with Momentum AI, which is in addition to their core suite of features including custom deal rooms. It is an AI summarization tool that emphasizes methodologies to help sales professionals drive their sales processes more effectively. With automated call summaries, CRM push integration, and pre-defined structures, Momentum allows sales teams to stay on top of their deals and maintain a more organized sales process.
One of the advantages of using Momentum is its focus on methodologies, which provides sales professionals with guidance on best practices and processes to follow for successful sales outcomes. This can be particularly helpful for teams that need more structure and direction in their sales approach.
However, there are several features that Momentum lacks compared to some of the other tools on this list. It does not offer emotional intelligence-based summaries, dialer input or a coherent structure in its summaries. These missing features could make Momentum less appealing to sales professionals who require a more comprehensive set of capabilities from their AI summarization tool, as well as those that value usability and accuracy over being integrations-rich.
Pros:
Cons:
Starter: $29 per user per month
Business: $69 per user per month
Transformation: $99 per user per month
Includes platform fee
Winn is an AI summarization tool that records updates to Salesforce fields in real-time and generates call summaries as well. Winn has a sharp focus on CRM updates, and supports sales methodology-based updates like MEDDICC from the get-go.
In addition to its user-defined structure capabilities, Winn also focuses on methodologies, providing guidance on best practices for successful sales outcomes. This can be particularly beneficial for teams that need more direction and structure in their sales approach.
However, based on experience from actual Winn users, it seems that while Winn definitely competes on feature-parity and a knack for marketing, the product maturity is pretty low. The call summaries and CRM updates are not the best-in-class and miss nuance, leading to relatively lower accuracy levels. The battle for the throne of the best call summarizer and assistant is still fresh, and it remains to be seen how Winn takes it forward in their product.
Pros:
Cons:
Pro: Starts at $69 per user per month
Enterprise: Custom pricing
Attention offers a unique chat interface for sales professionals, making it a more interactive and engaging AI summarization tool. It provides automated call summaries, pre-defined structures, CRM push integration, and even AI-generated follow-up emails, streamlining workflows and improving collaboration.
The chat interface makes Attention stand out from the other tools on this list, allowing sales professionals to interact with their AI assistant in a more conversational manner. This can lead to a more enjoyable and efficient user experience.
However, Attention has its limitations. It does not offer emotional intelligence-based summaries, user-defined structures, methodologies, or Slack push integration. These missing features might make Attention less appealing to sales professionals who require more than just a chatbot over calls.
Based on experiments by users, it seems that their summaries leave quite a bit wanting in terms of accuracy and a usable structure.
Pros:
Cons:
Not available publicly
Fathom focuses on providing sales professionals with a comprehensive CRM integration, offering automated call summaries, pre-defined structures, and a seamless push to the CRM. This focus on CRM integration makes it easier for sales teams to keep track of their deals and maintain an organized sales process, reducing much of the manual data entry that teams with heavy CRM-reliance have to deal with.
However, Fathom lacks some foundational features that other AI summarizers for sales on this list provide, such as emotional intelligence-based summaries, AI-generated follow-up emails, user-defined structures, methodologies, chat interfaces, and Slack push integration. Fathom’s summaries are also less accurate than most tools, and don’t have a good structure to organize them - and they end up being just a bullet point list with no sense of what’s more important than others, and what one needs to look at first for a quick recap. The lack of structure and low accuracy make their summaries just a checkmark, but not a game-changer, as call summaries should be, missing the mark on saving reps actual time while following up and filling in their managers on calls.
These missing features may make Fathom less suitable for sale pros looking for AI summarizers that do more than just data entry.
Fathom is an AI summarization tool designed to provide sales professionals with comprehensive CRM integration. Key features of Fathom include:
Pros:
Cons:
Free version: Available
Premium: $19 per user per month
Summarization is highly context and use-case dependent. A tool that excels at summarizing one type of content might struggle with another. For example, a summarizer designed for blog posts and web pages may perform poorly when summarizing conversations or legal reports. To choose the right summarization tool, consider the specific requirements of your use case and evaluate each tool's ability to address those needs.
There obviously are certain general-purpose summarizers like ChatGPT that can summarize a variety of types of text well. But when it comes to enterprise use cases like sales or critical use cases like medicine, a general-purpose summarizer’s accuracy and coverage would not be sufficient. These use cases would need specialized AI meeting summarizers tuned to their specific needs.
Here are a few aspects that you need to consider before investing in any AI summarizer:
It must know who is on the seller side and who is on the buyer side in any given conversation.
This includes identifying the unique language, terminologies, and jargon used in sales interactions. By recognizing the context, the summarizer can extract relevant information and create meaningful summaries. If it has context about the product being sold and previous conversation history with the specific buyer, the summaries could be way better.
An effective AI summarizer for sales calls should identify and highlight the most critical points discussed during the call, such as pain points, objections, solutions proposed, and any commitments made by either party. Additionally, it should also extract action items and follow-up tasks to ensure that sales reps can act on them promptly.
Understanding the sentiment and tone of the conversation is crucial for sales teams. A good AI summarizer should be able to analyze the emotions expressed during the call, providing insights into the prospect's feelings and attitudes towards the product or service being discussed.
Every sales team has its unique workflow and requirements. An AI summarizer should offer customization options, allowing users to tailor the summaries according to their needs, such as including specific data points, following a specific sales methodology, or integrating with other sales tools.
A good AI summarizer for sales calls should be user-friendly, with an intuitive interface that allows sales reps to access and understand the summaries quickly, without requiring extensive training or technical expertise. Ideally, it should integrate seamlessly with a CRM system, Slack, email, and the other tools that salespeople use on a daily basis.
These summaries should be used by the tool to do even more intelligent tasks, like auto-fill up of CRM, generation of follow-up emails after every call, recommended next steps beyond what was discussed in the call, deal strategy, etc. Futuristic, but totally relevant to sales.
When making a decision on the best AI summarization tool for your use case, it’s important to keep in mind what your key factors are - optimizing on price, capabilities, ability to out-innovate the market, ease of use and customizability would all be important factors in this evaluation.
It’s clear that AI meeting summarization tools are changing the way we consume and process information, particularly in the realm of sales calls and conversations. By understanding the unique challenges and requirements of summarizing sales conversations, AI-powered summarization tools can deliver concise, relevant, and actionable summaries that drive productivity and enable sales teams to focus on closing deals and nurturing relationships.
Sybill users are embracing AI summarization like never before. Staying ahead of the curve, building better relationships faster, and staying organized, informed, and efficient. All of it while saving 45 minutes to an hour every single day.
If you’re looking to evaluate the best AI summarization tool in the near future, do check out Sybill’s Magic Summaries. It’s got some real magic up its sleeve!
The post-ChatGPT world is well and truly here. AI-driven meeting summarizer tools are abundant, and we have more choice than ever to summarize any kind of text. All to make better decisions quickly, no matter what your source of text: hundreds of call transcripts, extensive research papers, expert articles and so much more. But how do you choose the best AI summarizer based on your use case?
Before I get into the quickly evolving world of text-based AI, let’s understand the basics.
AI-driven meeting summarization tools help us mortal humans digest vast amounts of information and present it in a concise, easy-to-consume format.
There are many business reasons to use AI summarizers, and I’ll get into those in just a bit. But for now, let’s imagine Sarah, a busy SaaS entrepreneur who has hundreds of calls and meetings as she builds her team and business from the ground up.
Every day, Sarah is inundated with tens of call transcripts, some with her prospective employees and many with business prospects and partners. A hundred emails, at the minimum. She must also keep up with the trends and news in her industry and community. There’s always something going on and she can’t help but wonder if she’s missing some piece of important information she needs in life or business.
A day in the life of Sarah, without the best AI summarizer ;)
Sarah loves her work, sure. But likes having time to herself even more. Where’s the time for that, though? Well, she can and hopefully does, find that time with AI summarizers :)
AI meeting summarizer tools are innovative applications that condense large volumes of text into concise, easily digestible summaries. With AI superpowers, these tools have an uncanny ability to identify and extract the most crucial points, presenting them in a clear and structured format, reshaping the way people consume information, making the process far more efficient and enjoyable.
In a world where the importance of timely and accurate information keeps growing, AI summarizer tools are indispensable to make better decisions, know and understand more, and achieve a semblance of work life balance!
Full disclosure. Text summarization is pretty close to my heart. I started out working in natural language processing during a winter internship at Stride.ai, where I worked on text summarization models for news. That project helped me go deep into the topic, and I ended up working on summarization in a variety of projects after that in school, work, and eventually in my own startup, Sybill.
In this guide, I dive into the different kinds of summarization, the top use cases for it, and the most popular AI summarizer tools for each use case. The meeting summarizing space is evolving very quickly, since there are new AI tools developed and deployed every single day, and a new summarizer every week that’s based on some alteration in a popular large language model (LLM). I hope you’ll get a lot out of this guide as you make your own choices.
Before we dive into the best AI summarization tools, let’s look into what we exactly mean when we talk of a summary. There are two technical ways in which a summary is created:
Extractive summarization selects key sentences or phrases from the original text to form a summary. While it preserves the text's original wording, the summaries can sometimes lack fluidity or omit crucial context.
When you pick out the most important or representative quotes from a graduation speech, it’s a form of extractive summarization.
Abstractive summarization rephrases and restructures the original text to craft a summary. This method produces smoother summaries that encapsulate the text's essence, but it might occasionally introduce errors or stray from the original content.
When you go home after work and tell your partner or friend about how your day was, that's an abstractive summary.
Hybrid summarization combines elements of both extractive and abstractive summarization. It first identifies the key sentences or phrases (extractive approach) and then rephrases or restructures them (abstractive approach) to create a coherent and concise summary. This method aims to leverage the strengths of both techniques to produce more accurate and fluid summaries.
Imagine you are summarizing a detailed project report. You select the most important sections and key points (extractive) and then rewrite them in a cohesive narrative that highlights the project's progress and outcomes (abstractive).
ChatGPT, powered by OpenAI, is a popular AI summarizer for general-purpose text. It excels at generating coherent and concise summaries while maintaining the overall meaning of the source text. You can also tune the length, the tone, and the focus of the summary by cleverly prompting it and stating your intent. There’s little surprise that this magic summarizer, available for less than a few McDonald’s meals, has over 100 million users and a base that keeps growing exponentially every day!
But there’s a catch. ChatGPT may generate summaries that deviate from the original content or introduce inaccuracies. It might also miss important details from summaries. It’s not quite equipped to understand what a domain-specific important detail is. For instance, a prospect might mention in a sales call that they use Salesforce as their CRM system, but if that’s the only sentence in a 45-minute call that references this fact, ChatGPT may fail to pick it up while summarizing the call, since it doesn’t know that could be an important detail for the salesperson.
Pros:
Cons:
Free plan: $0 per user per month
Plus plan: $20 per user per month
Overall, while ChatGPT is a powerful tool for general summarization tasks, it may not be the best choice for highly specialized or domain-specific needs without careful prompting and adjustments.
QuillBot is a versatile AI summarizer that works well for general-purpose text summarization. It offers multiple modes, including standard, creative, and formal, to cater to various content types. However, it may not always provide the most accurate summaries, especially when dealing with complex or niche topics.
Source: Quillbot website
PS: QuillBot has also nailed the SEO game for AI summarizers, and I tend to be a little skeptical of the tools that do because their superior SEO position gives them a chance over the long term not to be the innovation leader and still get the required demand. However, I recommend you try it out for yourself and figure out if it’s a good fit for your use case. QuillBot recently wrote about how it can work together with ChatGPT. I personally don’t find the arguments convincing enough - whatever it says that QuillBot can do (summarize, paraphrase, etc.) on top of ChatGPT output is something ChatGPT can also do by itself. However, plagiarism detection and citations might be interesting topics to look into if you’re considering QuillBot.
QuillBot recently wrote about how it can work together with ChatGPT. I personally don’t find the arguments convincing enough - whatever it says that QuillBot can do (summarize, paraphrase, etc.) on top of ChatGPT output is something ChatGPT can also do by itself. However, plagiarism detection and citations might be interesting topics to look into, if you’re considering QuillBot.
Pros:
Cons:
Free: $0 per user per month
Premium: $9.95 per user per month
Overall, QuillBot is a solid choice for general-purpose summarization and offers some unique features, but it may not be the best option for specialized or highly complex texts.
Otter.ai has established itself as one of the best end-user-facing transcription tools out there. It has a low word error rate, a decent way of matching statements to speakers, and doesn’t generally crash. But is Otter a good bet for call summaries?
Depends on how good you want your AI summarizer to be in the context of conversations.
For example, the above is a summary of a call that I had, discussing a content writer position in my startup, Sybill. As you can see, it’s not really a summary.
Otter produces an outline of the conversation, sort of like creating chapters. And the chapters are decent, but they don’t add up to a summary at all. They are pointers to specific timestamps in the transcript.
If that’s what you want, and you’re okay listening to the call transcript later on, Otter might work for you. If you really want a summary that’s both accurate and covers the gist of the call without having you watch or listen to the call, then Otter’s summaries fall short.
Pros:
Cons:
Basic plan: Free
Pro plan: $8.33 per user per month
Business plan: $20 per user per month
Enterprise plan: Custom
Overall, Otter is a robust tool for transcription with real-time capabilities and good speaker identification. However, it may fall short in providing comprehensive and accurate summaries of conversations.
Fireflies.ai is another popular meeting transcription software with a slick UI. It excels in the number of integrations it has with meeting providers, and the number of supported languages. Let’s look at the summaries now:
As you can see, the summary includes a few key pointers from the meeting. It’s a pretty good starting point for summarizing general-purpose meetings. You can read more about their summarization and how they compare in their own article.
However, Fireflies suffers the same issue that AI summarizers at the heart of meeting providers like MS Teams suffer: their summaries are general purpose. They include key pointers like tasks, decisions and next steps, but don’t capture domain-specific information.
For example, a user research-focused summarizer would have a section that captures feature requests. A sales-focused summarizer would have a section that captures the prospect’s areas of interest. A customer support-focused summarizer would have a section that captures customer pain points with their usage of the product or service.
Pros:
Cons:
Free: $0 per seat per month
Pro: $10 per seat per month
Business: $19 per seat per month
Enterprise: $39 per seat per month
Overall, Fireflies is a strong contender in the meeting transcription space, offering extensive integrations and multilingual support. However, its general-purpose summaries may not meet the specific needs of specialized domains, making it less effective for certain use cases.
You get the drill. And this brings us to…
I am one of the founders, so I could be biased. G2 users, on the other hand…
Let’s see how Sybill does against the criteria that I highlighted above.
Sybill has a lot of context about conversation participants (their role, their LinkedIn profile, call metadata, and more), and a pretty good level of conversation and company context as well.
It captures all the key points of interest, pain points, and points of hesitation or objections from calls in neat sections. The summaries come right into your email and Slack, as well as get pushed into your CRM systems automatically tagged to the right opportunity, company, and contact.
Sybill is also the only sales summarization tool in the market that captures and synthesizes insights from video data. It captures participant engagement and excitement levels by quantifying their non-verbal reactions throughout the call, which provides key insights into all buyers’ interest points and areas where they didn’t really care.
Behavior AI + Generative AI = best-in-class call summaries.
Sybill also supports the customization of call summaries for various RevOps teams like customer success, sales, and product.
Sybill was the first sales intelligence tool to introduce structured call summaries and will continue to maintain the innovator’s lead. We’re building Sybill to be the all-in-one personal assistant for sales professionals.
Oh, and before I forget. Sybill also crafts an automated follow-up email from the summaries that it generates, so you can send a follow-up with just a click. It’s shown to save 45-60 mins per day in follow-ups and note-taking for an average SaaS sales rep.
The only con? Starting at $59, it could be a little pricey for small businesses but that pricing comes for the best-in-class 95% accuracy that Sybill offers in return.
Pros:
Cons:
Starter: $59 per user per month
Mind Reader: $65 per user per month
Enterprise: Custom pricing
Overall, Sybill stands out as a powerful AI meeting summarizer, particularly for sales teams, due to its high contextual understanding, video insights, and automation capabilities. While it may be a bit pricey for some, the advanced features and time savings it offers make it a valuable investment for many businesses.
Avoma summarizes sales calls neatly into various sections as well. It’s a meeting intelligence platform and aims to assist sellers before, during, and after each meeting. It fairs pretty well on having participant context, and capturing key takeaways from meetings.
Avoma integrates pretty well with CRM systems (they don’t mention a Slack integration on their website) as well and allows category customization in the summaries.
Avoma doesn’t capture participant reactions during the call, and therefore its summaries only focus on the most important takeaways from the transcript, rather than focusing on the trifecta of the transcript, audio tonality, and video.
Avoma also doesn’t create follow-up emails from summaries or surface any recommended next steps based on deal context.
Overall, it’s a good call recording and summarization tool. However, the lack of capabilities in taking advantage of the summary for actionable next steps like email creation, and the unavailability of insights based on buyer engagement and excitement levels makes its price tag seem a little steep.
Pros:
Cons:
Basic: $0 per user per month
Starter: $19 per user per month
Plus: $49 per user per month
Business: $79 per user per month
Enterprise: $129 per user per month
Overall, Avoma is a solid choice for call recording and meeting summarization, especially for teams needing structured and customizable summaries. However, its lack of multimodal capabilities and actionable insights may be a drawback for some users, particularly given its price.
Momentum recently came up with Momentum AI, which is in addition to their core suite of features including custom deal rooms. It is an AI summarization tool that emphasizes methodologies to help sales professionals drive their sales processes more effectively. With automated call summaries, CRM push integration, and pre-defined structures, Momentum allows sales teams to stay on top of their deals and maintain a more organized sales process.
One of the advantages of using Momentum is its focus on methodologies, which provides sales professionals with guidance on best practices and processes to follow for successful sales outcomes. This can be particularly helpful for teams that need more structure and direction in their sales approach.
However, there are several features that Momentum lacks compared to some of the other tools on this list. It does not offer emotional intelligence-based summaries, dialer input or a coherent structure in its summaries. These missing features could make Momentum less appealing to sales professionals who require a more comprehensive set of capabilities from their AI summarization tool, as well as those that value usability and accuracy over being integrations-rich.
Pros:
Cons:
Starter: $29 per user per month
Business: $69 per user per month
Transformation: $99 per user per month
Includes platform fee
Winn is an AI summarization tool that records updates to Salesforce fields in real-time and generates call summaries as well. Winn has a sharp focus on CRM updates, and supports sales methodology-based updates like MEDDICC from the get-go.
In addition to its user-defined structure capabilities, Winn also focuses on methodologies, providing guidance on best practices for successful sales outcomes. This can be particularly beneficial for teams that need more direction and structure in their sales approach.
However, based on experience from actual Winn users, it seems that while Winn definitely competes on feature-parity and a knack for marketing, the product maturity is pretty low. The call summaries and CRM updates are not the best-in-class and miss nuance, leading to relatively lower accuracy levels. The battle for the throne of the best call summarizer and assistant is still fresh, and it remains to be seen how Winn takes it forward in their product.
Pros:
Cons:
Pro: Starts at $69 per user per month
Enterprise: Custom pricing
Attention offers a unique chat interface for sales professionals, making it a more interactive and engaging AI summarization tool. It provides automated call summaries, pre-defined structures, CRM push integration, and even AI-generated follow-up emails, streamlining workflows and improving collaboration.
The chat interface makes Attention stand out from the other tools on this list, allowing sales professionals to interact with their AI assistant in a more conversational manner. This can lead to a more enjoyable and efficient user experience.
However, Attention has its limitations. It does not offer emotional intelligence-based summaries, user-defined structures, methodologies, or Slack push integration. These missing features might make Attention less appealing to sales professionals who require more than just a chatbot over calls.
Based on experiments by users, it seems that their summaries leave quite a bit wanting in terms of accuracy and a usable structure.
Pros:
Cons:
Not available publicly
Fathom focuses on providing sales professionals with a comprehensive CRM integration, offering automated call summaries, pre-defined structures, and a seamless push to the CRM. This focus on CRM integration makes it easier for sales teams to keep track of their deals and maintain an organized sales process, reducing much of the manual data entry that teams with heavy CRM-reliance have to deal with.
However, Fathom lacks some foundational features that other AI summarizers for sales on this list provide, such as emotional intelligence-based summaries, AI-generated follow-up emails, user-defined structures, methodologies, chat interfaces, and Slack push integration. Fathom’s summaries are also less accurate than most tools, and don’t have a good structure to organize them - and they end up being just a bullet point list with no sense of what’s more important than others, and what one needs to look at first for a quick recap. The lack of structure and low accuracy make their summaries just a checkmark, but not a game-changer, as call summaries should be, missing the mark on saving reps actual time while following up and filling in their managers on calls.
These missing features may make Fathom less suitable for sale pros looking for AI summarizers that do more than just data entry.
Fathom is an AI summarization tool designed to provide sales professionals with comprehensive CRM integration. Key features of Fathom include:
Pros:
Cons:
Free version: Available
Premium: $19 per user per month
Summarization is highly context and use-case dependent. A tool that excels at summarizing one type of content might struggle with another. For example, a summarizer designed for blog posts and web pages may perform poorly when summarizing conversations or legal reports. To choose the right summarization tool, consider the specific requirements of your use case and evaluate each tool's ability to address those needs.
There obviously are certain general-purpose summarizers like ChatGPT that can summarize a variety of types of text well. But when it comes to enterprise use cases like sales or critical use cases like medicine, a general-purpose summarizer’s accuracy and coverage would not be sufficient. These use cases would need specialized AI meeting summarizers tuned to their specific needs.
Here are a few aspects that you need to consider before investing in any AI summarizer:
It must know who is on the seller side and who is on the buyer side in any given conversation.
This includes identifying the unique language, terminologies, and jargon used in sales interactions. By recognizing the context, the summarizer can extract relevant information and create meaningful summaries. If it has context about the product being sold and previous conversation history with the specific buyer, the summaries could be way better.
An effective AI summarizer for sales calls should identify and highlight the most critical points discussed during the call, such as pain points, objections, solutions proposed, and any commitments made by either party. Additionally, it should also extract action items and follow-up tasks to ensure that sales reps can act on them promptly.
Understanding the sentiment and tone of the conversation is crucial for sales teams. A good AI summarizer should be able to analyze the emotions expressed during the call, providing insights into the prospect's feelings and attitudes towards the product or service being discussed.
Every sales team has its unique workflow and requirements. An AI summarizer should offer customization options, allowing users to tailor the summaries according to their needs, such as including specific data points, following a specific sales methodology, or integrating with other sales tools.
A good AI summarizer for sales calls should be user-friendly, with an intuitive interface that allows sales reps to access and understand the summaries quickly, without requiring extensive training or technical expertise. Ideally, it should integrate seamlessly with a CRM system, Slack, email, and the other tools that salespeople use on a daily basis.
These summaries should be used by the tool to do even more intelligent tasks, like auto-fill up of CRM, generation of follow-up emails after every call, recommended next steps beyond what was discussed in the call, deal strategy, etc. Futuristic, but totally relevant to sales.
When making a decision on the best AI summarization tool for your use case, it’s important to keep in mind what your key factors are - optimizing on price, capabilities, ability to out-innovate the market, ease of use and customizability would all be important factors in this evaluation.
It’s clear that AI meeting summarization tools are changing the way we consume and process information, particularly in the realm of sales calls and conversations. By understanding the unique challenges and requirements of summarizing sales conversations, AI-powered summarization tools can deliver concise, relevant, and actionable summaries that drive productivity and enable sales teams to focus on closing deals and nurturing relationships.
Sybill users are embracing AI summarization like never before. Staying ahead of the curve, building better relationships faster, and staying organized, informed, and efficient. All of it while saving 45 minutes to an hour every single day.
If you’re looking to evaluate the best AI summarization tool in the near future, do check out Sybill’s Magic Summaries. It’s got some real magic up its sleeve!