As of September 2026, Latka tracks 1 video AI agents SaaS companies with $100M+ in annual revenue. They have combined revenues of $1B and employ 200 people. They have raised $485.6M.
Every company below sells video AI agents software to other businesses and is ranked by its most recent annual revenue. Revenue, funding, headcount and customer figures come from CEO interviews on the Latka podcast, public company filings, and Latka estimates where a company has not disclosed a number.
Video AI Agents utilize artificial intelligence to analyze, interpret, and respond to video content in real-time. These agents can incorporate features such as object recognition, facial analysis, and visual question answering, which facilitate a variety of applications, including security surveillance, marketing analytics, and customer engagement. Typically, users include organizations in sectors like retail, security, and entertainment who seek to enhance their operational efficiency and gain insights from visual data. In practical terms, Video AI Agents can streamline workflows by automating tasks such as video moderation and content tagging, allowing businesses to focus on strategic decisions rather than manual processes. Common buyer personas for these solutions often include operations managers, marketing professionals, and IT directors who are trying to leverage video data for improved decision-making and customer interactions.
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Showing 1 of 1 companies ranked by annual revenue.
San Francisco, California, United States
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Latka tracks 1 video AI agents SaaS companies with $100M+ in annual revenue. Together they generate $1B in annual revenue and employ 200 people.
Mercor is the largest, with $1B in annual revenue, founded in 2023.
The average video AI agents SaaS company in this list makes $1B a year, across 1 companies with reported revenue.
Ranked by annual revenue, the leaders are Mercor.
The 1 video AI agents SaaS companies with $100M+ in annual revenue tracked here have raised $485.6M in disclosed funding between them.
- Must offer real-time video analysis capabilities - Should include features for object and facial recognition - Must be able to automate the extraction of insights from video content - Must support integration with existing analytics and management systems - Not just focused on video editing; must also provide AI-driven insights and automation
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