Dig launched in 2021 in Tel Aviv and initially helped marketing teams compress and repurpose video content into short-form social clips. The company pivoted to focus on detecting influencer-driven disinformation amid rising geopolitical conflicts. Dig developed an in-house tech stack using proprietary large language models to identify posts across video, image, and text that relate to specific brands. The platform analyzes content to flag reputational risks such as deepfakes, disinformation, and counterfeit product selling while accounting for humor and sarcasm to reduce false positives. Dig raised a $14 million Series A led by New Era Capital Partners and Osage Venture Partners.
For years, marketers have employed social listening technology to help them understand what is being said about their brands in text formats on blogs and forums. But social listening on video on apps like TikTok, YouTube, and Instagram is a more complicated and expensive process. That's because it requires natural language processing and other computing costs involved with processing video, Familier said.
Dig built a tech stack that uses its own large language models to identify posts across video, image, and text related to a particular brand. Dig analyzes the content to flag any potential reputational or brand risks, such as deepfakes, disinformation, or content creators selling counterfeit products. It also accounts for humor and sarcasm to rule out false positives, the company said.
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