Meetings take a lot of time and there is no way around this problem. According to a 2022 survey by Representative.com, many American workers spend up to about eight hours in meetings each week, depending on the industry and region.
The impact on productivity explains the growing popularity of AI-based summary tools. In a recent survey of marketers by the Conference Board, a nonprofit think tank, nearly half of respondents said they use AI to summarize content in emails, conference calls and even more.
Although a number of video conferencing suites now offer built-in summarization capabilities, David Shim believes there is room for third-party solutions. And he would: He’s the co-founder of Read AI, which summarizes video calls on platforms like Zoom, Microsoft Teams, and Google Meet.
Shim, former CEO of Foursquare, co-founded Read AI with Rob Williams and Elliott Waldron in 2021. Before Read AI, the trio worked together at Foursquare, Snapchat, and Shim’s previous startup, Placed (which Foursquare acquired in 2019).
“Read AI’s direct competitor is traditional project management, where notes are written manually,” Shim told TechCrunch. “By learning what’s important to you across multiple platforms, Read is not a co-pilot, but rather an autopilot delivering content that makes your work more effective and efficient.”
At first, Read focused exclusively on video conferencing solutions, offering dashboards to measure how a meeting was going (as judged by some metrics, at least) and two-minute summaries of hour-long meetings. But, coinciding with Goodwater Capital’s recently closed $21 million funding round with Madrona Venture Group, the company is expanding into message and email digest.
Available as a “soft launch,” Read’s new feature connects to Gmail, Outlook, and Slack as well as video conferencing platforms to learn topics that might interest you. Within 24 hours of connecting to the messaging and video conferencing services you use, Read begins providing daily updates with summaries, AI-generated “takeaways,” insight into key content, and Updated conversation topics in chronological order. Read charges a monthly fee of $15 to $30 for its service.
“What makes Read unique is that its AI agents work silently in the background, allowing your meetings, emails and messages to interact with each other,” Shim said, adding that the average summary by Read AI condenses 50 emails sent to 10 recipients into one. summary. “This connected intelligence unifies your communications and allows you and your team to benefit from personalized, actionable briefings tailored to your needs and priorities.”
Now color me skeptical, but I’m not sure I trust any of them AI-powered tool to summarize content consistently and accurately.
Read’s platform leverages generative AI to summarize meetings, messages and emails. Image credits: Read
Models like ChatGPT and Microsoft’s Copilot make errors during summaries due to their tendency to hallucinate, including in meeting summaries. In a recent article, the Wall Street Journal cited a case where, for an early user using Copilot for meetings, Copilot invented the participants and implied that the calls were about topics that were never actually discussed .
Is the Read AI tool different? Shim claims it’s more robust than most solutions available, including competitors like Supernormal and Otter.
“Read uses a proprietary methodology to coordinate raw content with language model outputs, so that deviations are automatically detected and driven appropriately,” he said. “In addition, we can use meeting content to better contextualize the content of emails and messages, further reducing uncertainty and improving outcomes. »
Take this statement with a grain of salt. Shim did not share benchmark results to support these claims.
Instead of benchmarks, Shim pointed out the productivity-enhancing summary tools such as Read can (in theory) offer.
“Rather than rescheduling a meeting when you’re late or double-booked, Read can attend for you and provide you with a summary and action steps that even the best executive assistant couldn’t match,” he said, also emphasizing that Read does not use customer data to train its AI models and users have “full control” over the content flowing through the platform. “AI brings attention back to knowledge workers (by) saving them hours per day.”
Read AI is no stranger to controversy, so it’s a little It’s hard to take Shim at his word. The platform’s sentiment analysis tool, which interprets voice and facial signals from meeting participants to inform hosts of their feelings, has been criticized by privacy advocates for being too invasive, prone to bias and most likely a data security risk.
Gender and racial bias are a well-documented phenomenon in sentiment analysis algorithms.
Emotional analysis models tend to attribute more negative emotions to the faces of Black people than to those of White people, and to perceive the language that some Black people use as aggressive or toxic. AI video recruitment platforms have been found to react differently when the same candidate wears different outfits, such as glasses and a scarf. And in a 2020 study by MIT, researchers showed that algorithms could be biased toward certain facial expressions, like smiling, which could reduce their accuracy.
Image credits: Read
Perhaps tellingly, Shim continues to view Read’s sentiment analysis technology as a competitive advantage, this is not a risk, while emphasizing that customers can disable the feature and that analytics data is periodically deleted from Read’s servers. “Using a multimodal model allows Read to incorporate nonverbal responses into meeting summaries,” he said. “As an example, during a pitch meeting, a startup may talk about the benefits of the product, but attendees visually shake their heads and frown during the pitch… Read creates a personalized baseline of engagement and sentiment for each meeting participant, rather than applying a one-size-fits-all model, ensuring that each person is treated as a unique person.
Accurate or not, with a war chest of $32 million and a customer base that grew by half a million users in the last quarter, Read has clearly convinced some people that he can deliver on his promises.
Read, based in Seattle, Washington, plans to double its workforce to more than 40 employees by the end of the year, taking advantage of the new capital infusion, Shim said.
“In the face of a broader slowdown in recent years, Read continued to see the growth curve steepen in terms of users, meetings and revenue,” he added. “This acceleration in growth can directly be attributed to the quantifiable return users are seeing in time savings when using Read AI in their meetings.”
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