Sequoia India’s Surge backs AI-powered video creation platform Gan.ai in $5.2M funding

As many as 91% of consumers want to see more videos from brands, according to a recent survey by the startup Wyzowl, which says it surveyed more than 500 respondents. Google meanwhile reported in 2019 that 55% of consumers use videos in their purchasing decisions.

Though the data may be in both companies’ self-interest – Wyzowl is a video production company while Google and YouTube share a parent company —  video content is clearly becoming a more meaningful way for both small and large brands to reach new customers.

The good news for such brands is that thanks to the magic of generative AI, a spate of startups are making it easier for companies of every size to develop customized videos. Runway AI, for example, raised $50 million at a $500 million valuation back in December to empower creatives in a way that wasn’t possible previously.

Now San Francisco-headquartered startup called Gan.ai has also attracted the attention of investors. The outfit — which helps brands create tailored videos for their customers with an AI-powered video creation platform — just closed on $5.2 million in seed funding led by Surge, Sequoia Capital’s rapid scale-up program. Emergent Venture and other angel investors also joined the round.

Gan.ai’s video personalization software enables brands to record with an actor, add keywords to a script, and send personalized videos to their customers in one click. According to founder and CEO of Gan.ai Suvrat Bhooshan, Gan.ai allows users to create landing pages and shopping and payment options by integrating with Shopify, Calendly, Stripe, Hubspot and Salesforce.  

Bhooshan, who previously worked at Facebook AI Research (FAIR), says Gan.ai has more than 200 users, including over 40 enterprise customers like Samsung, Zomato, Vivo and Mobile Premier League. 

“Generative AI was not a buzzword [in 2021],” Bhoosian tells TechCrunch,  but even then, he continues, “it was obvious that its application in marketing and sales was going to be imminent. This is a huge industry and people are eager to test new innovations that can move the dial on direct revenue impact.”

Gan.ai has two types of clients. The first is corporations with large marketing teams like mobile manufacturers and consumer goods like food delivery companies, sports teams, and mobile gaming companies.

The second type of user is business professionals like realtors, mortgage agents, insurance agents, and enterprise SaaS sales representatives.  

The startup, which was founded in 2021 and now employs 35 people, generates revenues by charging a fee based on the number of videos users generate. 

Gan.ai is competing with, and growing alongside, a host of players in the AI video generator market in addition to Runway ML. 

According to Bhooshan, most of these players fall into one of two categories. There are startups that fully generate synthetic avatar videos. Synthesia and HourOne are such startups. Others — like Gan.ai  — work on changing key variables in a real video, he says.

The latter can be more complex, he suggests. For example, Gan.ai works on original human videos recorded by the actor and where even a 1% variance in voice or lip movement can be easily noticed, says Bhooshan. He also explains that while some peers require anywhere from 15 minutes to two hours of training data, Gan.ai requires just 2 minutes to train data for each speaker to learn the voice and lip movement.

Ultimately, he says, “We want to make this process instant and real-time, without even requiring any additional data to really make this widespread available and work as seamlessly as mail-merge works on text.”

That seed round should help. Indeed, Bhooshan says that much of the company’s focus is on R&D and improving its current offerings. With some money in the bank, the company also wants to expand the “U.S. go-to-market” team and line up more consumer brands, he adds.

Sequoia India’s Surge backs AI-powered video creation platform Gan.ai in $5.2M funding by Kate Park originally published on TechCrunch

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