Meetings are time consuming and there is no way around it. According to a 2022 poll by MP.com, many US workers spend up to eight hours in meetings each weekdepending on industry and location.
The productivity hit explains the growing popularity of AI-powered summary tools. In a recent survey of marketers by The Conference Board, a nonprofit think tank, nearly half of respondents said they used artificial intelligence to summarize the content of emails, conference calls and more.
While some video conferencing suites now offer built-in summarizing capabilities, David Shim believes there is room for third-party solutions. And he would: He’s its co-founder Read AIwhich summarizes video calls on platforms such as Zoom, Microsoft Teams and Google Meet.
Shim, previously CEO of Foursquare, co-founded Read AI with Rob Williams and Elliott Waldron in 2021. Prior to Read AI, the trio worked together at Foursquare, Snapchat, and Shim’s previous startup, Placed (which acquired by Foursquare in 2019).
“Read AI’s direct competition is traditional project management, where notes are written by hand,” Shim told TechCrunch. “By learning what’s important to you across platforms, Read isn’t a co-pilot—rather, it’s an autopilot that delivers content that makes your work more effective and efficient.”
At first, Read focused exclusively on video conferencing solutions, offering dashboards to measure how well a meeting was going (as judged by some metrics, at least) and two-minute summaries of hour-long meetings. But to coincide with a recently closed $21 million funding round led by Goodwater Capital with Madrona Venture Group, the company is expanding into message and email digests.
Available in soft launch, Read’s new feature connects to Gmail, Outlook and Slack as well as video conferencing platforms to learn about topics that may be relevant to you. Within 24 hours of connecting to your messaging and video conferencing services, Read begins providing daily updates with summaries, AI-generated takeaways, an overview of key content, and updates on chronological conversation topics. Read charges a monthly fee of $15 to $30 for its service.
“What makes Read unique is that its AI agents work quietly in the background, allowing your meetings, emails and messages to interact with each other,” Shim said, adding that the average summary from Read AI condenses 50 email to 10 recipients in a single summary. “This connected intelligence unifies your communications and empowers you and your team with personalized, actionable updates tailored to your needs and priorities.”
Now, color me skeptical, but I’m not sure I trust Any AI-powered tool to summarize content consistently and accurately.
Read’s platform taps into the creation of artificial intelligence to summarize meetings, messages and emails. Image Credits: Reading
Models like ChatGPT and Microsoft’s Copilot they make mistakes when summarizing due to their tendency to hallucinate, including meeting summaries. In a recent article, The Wall Street Journal refers a case where, for an early adopter 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 many of the solutions out there, including rivals like Supernormal and Otter.
“Read performs a proprietary methodology to coordinate raw content with language model outputs so that discrepancies are automatically detected and guided appropriately,” he said. “Additionally, we can use content from meetings to better shape email and message content, further reducing uncertainty and improving results.”
Take this statement with a grain of salt. Shim did not share benchmark results to support these claims.
Instead of benchmarks, Shim emphasized the productivity-enhancing summarizing tools that Read can (theoretically) offer.
“Instead of rescheduling a meeting as you’re late or double-booked, Read can attend in your place and deliver a summary and action items 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 that users are in “full control” of the content that passes through the platform. “Artificial intelligence is putting the focus back on knowledge workers [by] saving them hours in the day.”
Read AI is no stranger to controversy, so it’s a a little bit hard to take Sim at his word. The platform’s sentiment analysis tool, which interprets the voice and facial cues of meeting participants to inform hosts about their sentiment, called outside of privacy advocates overly invasive, prone to bias and quite possibly a data security risk.
Gender and race prejudices area Good–documented phenomenon in emotion analysis algorithms.
Sentiment analysis models tend to outsource more negative emotions in the faces of blacks rather than whites, and Realize the language that some Black people use as offensive or toxic. AI video recruiting platforms have were found responding differently to the same job applicant by wearing different clothing, such as glasses and headscarves; And in 2020 study from MIT, the researchers showed that algorithms could become biased towards certain facial expressions, such as smiling, which could reduce their accuracy.
Image Credits: Reading
Perhaps tellingly, Shim continues to see Read’s sentiment analysis technology as a competitive advantage, is not a risk, while noting that customers can disable the feature and that analysis data is periodically deleted from Read’s servers. “Using a multimodal model allows Read to incorporate non-verbal responses into meeting summaries,” he said. “For example, during a pitch meeting, a startup might talk about the benefits of the product, but the participants visually shake their heads and frown during the pitch… Read creates a customized basis of engagement and emotion for each participant in meeting, rather than applying a one-size-fits-all model, ensuring that each person is treated as a unique individual.”
Accurate or not, with a $32 million war chest and a customer base that grew by half a million users last quarter, Read clearly has some convinced it can deliver on its promises.
Read, based in Seattle, Washington, plans to double its staff to more than 40 employees by the end of the year, capitalizing on the new capital infusion, Shim said.
“In the face of a broader slowdown in recent years, Read has continued to see the growth curve steepen in users, meetings and revenue,” he added. “This acceleration in growth can be directly attributed to the measurable performance that users are seeing in terms of time savings when using Read AI in their meetings.”
