Ai-powered Videoconferencing Platform Headroom Raises $9m – Techcrunch

By | 26/08/2022

Headroom, a startup developing AI-powered software to make meetings ostensibly more efficient, today announced that it raised $9 million in funding led by Equal Opportunity Ventures with participation from Gradient Ventures, LDV Capital, AME Cloud Ventures, and Morado Ventures. CEO Julian Greenish said that the proceeds volition be put toward product evolution and expanding the company’s workforce.

During the pandemic, virtual meetings became the de facto method of collaborating and connecting — both inside and exterior of the workplace. The momentum isn’t slowing downwardly. A 2020 IDC study projected that the videoconferencing market would grow to $9.7 billion in 2021, with 90% of Northward American businesses probable to spend more than on it. But in an interview with TechCrunch, Green argued that videoconferencing as it exists for most companies today just can’t supervene upon the intimacy of modest, focused coming together groups. He pointed to a Harvard Business Review survey, which revealed that 65% of senior managers felt meetings kept them from completing their own work while 64% said that they came at the expense of “deep thinking.”

“The legacy videoconferencing players are struggling to innovate beyond the disruptive shift from customer-based messaging architectures to depression-latency, hardware-accelerated, cloud-based existent-time AI on real-time communication streams,” Dark-green said via email. “There has been a tedious rollout of AI features (e.g., captions, dissonance cancellation), even though all acknowledge that AI features are demanded by users and the time to come of virtual meetings.”

Alongside Andrew Rabinovich, Green launched Headroom (non to be confused with Max Headroom) in 2020 to accost what he perceives equally the outstanding blockers in the videoconferencing industry. Light-green was previously the director at Google’s experimental 10 division and co-cofounded Houzz, an online interior pattern platform. Rabinovich was the head of AI at Magic Leap, the well-funded augmented reality startup, and prior to that he was a Google software engineer focused on estimator vision.

“[We] wanted to enable remote piece of work past making meetings smart and making coming together information useful,” Green said. “Headroom competes with the fragmented videoconferencing and meeting tools that people patch together to join, take notes in and send recaps of meetings … Having a shareable institutional retention of meetings reduces meeting duplication, and repetition, which is a major elevate on enterprise productivity and employee happiness.”

Headroom uses AI to power features similar automatic transcripts and meeting summaries, which remain indexable later on meetings with search filters for attendees, notes and topics. The platform offers full meeting replays and auto-generated highlight reels with key moments and activity items, plus AI-powered upscaling and quick reactions like “thumbs upward” and “wave” that participants can use during meetings.

But one of the more unique things most Headroom is its extensive analytics capabilities. The app tries to quantify “existent-fourth dimension meeting energy” by analyzing video, sound and text of and from various attendees. It even tracks center movements and hand and head poses, attempting to figure out the sentiment in a person’s exchanges.

Headroom

Image Credits:
Headroom

Sound a little dystopian? Perhaps. Setting that bated for a moment, there’s the matter of bias, which makes sentiment analysis an imperfect science at all-time. For example, research has shown that some of the datasets used to develop sentiment assay algorithms associate words similar “Black” with negative sentiments. The issue is systems that are more likely to flag a Black person’s speech with problematic descriptors (due east.m., “deplorable”) than a white person’due south.

Advocacy groups generally aren’t bullish on sentiment tracking. When Zoom introduced it as a feature for sales training, 28 human rights organizations wrote an open alphabetic character to the company request it to halt the software, calling it “discriminatory, manipulative [and] potentially dangerous” — and pointing out that it’south based on the flawed supposition that markers like vox patterns and body language are uniform for all people.

On the privacy front, Green said that only people who’ve been given admission to the analytics data, similar fellow meeting invitees or those with the appropriate permissions, can access it through Headroom. (Data is stored in the cloud; Headroom says it’southward pursuing, but doesn’t yet have, SOC 2 Blazon 2 certification.) Meeting organizers tin can choose to restrict meeting data further amongst those they invite, and — perchance well-nigh chiefly — any user can request to have their information deleted “in all forms.”

Dark-green said that combating bias is an ongoing area of study for Headroom also, admitting a wide one. While revealing little nigh Headroom’s sentiment assay technologies, he highlighted the platform’south efforts to apply feedback from coming together participants to improve its various algorithms, including for meeting summaries.

“[Headroom quantifies] participant engagement with real-time wordshare, affecting computing and eye tracking to give all participants a chance to engage to ensure more equal and diverse meetings,” Light-green said. “Headroom’south approach to real-fourth dimension meeting understanding is based on multimodal AI … Our model leverages inductive bias to disambiguate nuances and capture cardinal moments in conversations.”

Headroom’s policies might not abate every would-be user’s fears. Simply one might argue that the larger threat to the company, at least right now, are household-name rivals similar Microsoft Teams, Google Run into and Zoom. Nvidia threw its hat into the ring two years ago with Maxine, which makes heavy use of AI to deliver features like dissonance cancellation and face up relighting. On the other end of the spectrum, startups like Fireflies.ai and Read.ai are taking the plug-in approach, integrating with existing videoconferencing platforms to bulldoze meeting transcriptions and other “intelligent” features.

Headroom

Image Credits:
Headroom

With a focus on growth over profit, San Francisco–based Headroom, which has 14 employees, has remained costless and without usage or storage caps since launch. Green says that information technology currently has around v,000 users — far brusk of Zoom’s hundreds of millions. But he stresses that (1) Headroom isn’t necessarily trying to compete with platforms similar Zoom, preferring to focus on the pocket-size- and medium-sized business niche, and (two) it’due south early days for the platform.

“The global pandemic, remote work, and at present a hybrid workforce showed us everything that is wrong with meetings. No matter your visitor’s return to piece of work policy, remote teams need improve meetings and the power to search, review and share meeting information,” Green said. “The Headroom team experimented throughout [the pandemic] on how to make meetings better for remote teams, and is flexible to virtual, hybrid, in person, synchronous and asynchronous. A hybrid workforce is the new norm, so Headroom will continue to deliver a platform that evolves with where and how people are working.”

Source: https://techcrunch.com/2022/08/25/ai-powered-videoconferencing-platform-headroom-raises-9m/