Meetings are time consuming and there is no way around it. According to a 2022 poll, many U.S. workers spend up to around eight hours a week in meetings, depending on industry and location.

This decline in productivity explains the growing popularity of AI-driven summarization tools. In a recent survey of marketers by the nonprofit think tank The Conference Board, nearly half of respondents said they were using artificial intelligence to summarize emails, conference calls and more.

While many video conferencing suites now offer built-in summarization capabilities, David Shim believes there is room for third-party solutions. He does: He’s the co-founder of Read AI, a company that summarizes video calls on platforms like Zoom, Microsoft Teams, and Google Meet.

Shim, the former CEO of Foursquare, co-founded Read AI in 2021 with Rob Williams and Elliott Waldron. Before founding Read AI, the trio worked at Foursquare, Snapchat and Shim’s previous startup Placed (which Foursquare acquired in 2019).

“Read AI’s direct competition is traditional project management, where notes are written manually,” Shim told TechCrunch. “By understanding what’s important to you across platforms, Read is no longer a co-pilot but an autopilot, delivering content to make your work more effective and efficient.”

Initially, Read focused solely on video conferencing solutions, providing dashboards to measure how meetings were going (at least based on some metrics) and two-minute summaries of hour-long meetings. However, coinciding with the recent completion of a $21 million funding round led by Goodwater Capital and Madrona Venture Group, the company is expanding into messaging and email summarization.

Read’s new feature, now in “soft launch,” 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 the messaging and video conferencing services you use, Read starts delivering daily updates, including summaries, AI-generated “takeaways,” overviews of key content, and chronological updates on conversation topics. Read’s service costs $15 to $30 per month.

“Read is unique in that its AI agents work quietly in the background to enable your meetings, emails and messages to interact with each other,” Shim said, adding that Read AI’s average digest will be 10 recipients. 50 people’s emails compressed into a single summary. Generalization. “This connected intelligence unifies your communications and provides you and your team with personalized, actionable briefings tailored to your needs and priorities. ”

Now, makes me doubt it, but I’m not sure I trust it any AI-powered tools summarize content consistently and accurately.

Read Artificial Intelligence

Read’s platform uses generative artificial intelligence to summarize meetings, messages and emails. Image Source: read

Models like ChatGPT and Microsoft’s Copilot make mistakes when summarizing because they are prone to hallucinations, including in meeting summaries. In a recent article, the Wall Street Journal cited an example of an early adopter using Copilot to conduct meetings where Copilot invented fictional attendees and suggested the call covered topics that were never actually discussed.

Are Read AI’s tools different? Shim claims it’s more powerful than many solutions, including competitors like Supernormal and Otter.

“Read runs a proprietary method to reconcile raw content with language model output so that deviations are automatically detected and directed appropriately,” he said. “Additionally, we can use meeting content to better understand the context of email and message content, further reducing uncertainty and improving outcomes.”

Take this statement with a grain of salt. Shim did not share benchmark results to support these claims.

Shim emphasizes that summary tools like Read can (in theory) provide productivity gains, not benchmarks.

“Rather than rescheduling a meeting when you’re late or double-booked,” he says, “Reed can sit in for you in meetings and provide you with summaries and action items that even the best administrative assistant can’t match.” Reed does not use customer data to train its AI models, and users have “full control” of content that goes through the platform. “AI is refocusing attention on knowledge workers [by] Save them a few hours every day. “

Reading AI is no stranger to controversy, so here’s one small It’s hard to believe Shim’s words. The platform’s sentiment analysis tool can interpret meeting participants’ vocal and facial cues to inform moderators of their emotions, but privacy advocates have criticized the tool as being too intrusive, prone to bias and likely to pose data security risks.

Gender and racial bias is a well-documented phenomenon in sentiment analysis algorithms.

Sentiment analysis models tend to assign more negative emotions to black people than white people and view some language used by black people as offensive or toxic. Research has found that AI-powered video recruiting platforms react differently to the same job candidate wearing different attire, such as glasses and a headscarf. Research from MIT in 2020 suggested that algorithms may be biased toward certain facial expressions, such as smiling, which could reduce their accuracy.

Read Artificial Intelligence

Image Source: read

Perhaps tellingly, Shim continues to view Read’s sentiment analysis technology as a Competitive Advantagenot a risk, while noting 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. “For example, in a pitch meeting, a startup might talk about the benefits of the product, but participants will visually shake their heads and frown during the pitch… Reading creates a customized engagement for each meeting participant and emotional baselines, rather than applying one-size-fits-all models, ensuring each person is treated as a unique person. “

Accurate or not, Read has $32 million in funding and a customer base that grew by 500,000 users in the past quarter, clearly leading some to believe it can deliver on its promises.

Seattle, Washington-based Read plans to use the new infusion of capital to double its headcount to more than 40 employees by the end of the year, Shim said.

“In the face of the broader economic slowdown of the past few years, Read’s growth curve for users, meetings and revenue continues to steepen,” he added. “This acceleration in growth can be directly attributed to users using Read AI in meetings Quantifiable return on time saved.”

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