TwelveLabs Secures $100M Series B: Pioneering Video Superintelligence
July 8, 2026, 3:48 pm
TwelveLabs secured $100M Series B funding. This investment propels their "video superintelligence" mission. The company builds a full-stack agentic intelligence system. It combines perception, knowledge, and reasoning for video. Funds target aggressive R&D in San Francisco and Seoul. They also support global expansion, opening new offices in New York and London. Core technology, Marengo 3.0 and Pegasus 1.5, natively understands video content. They transform raw footage into structured, searchable data for AI systems. A deepened strategic partnership with Amazon Web Services ensures optimized performance on Trainium chips. This empowers industries—media, government, security, sports, automotive—to unlock insights from massive video archives. Total funding now exceeds $207M, highlighting strong investor confidence.
TwelveLabs charts a bold new course. The video intelligence company just announced a substantial $100 million Series B funding round. This capital infusion significantly accelerates its drive toward "video superintelligence." It marks a pivotal moment for AI's capability in understanding the visual world.
The investment round saw robust participation. NEA and NAVER Ventures co-led the funding. Esteemed investors like Amazon, Radical Ventures, Korea Investment Partners, Index Ventures, Quadrille Capital, and Red Bull Ventures joined. This latest round pushes TwelveLabs' total funding beyond $207 million. Such backing underscores deep confidence in the company's vision and technology.
Funds will fuel aggressive expansion. TwelveLabs plans significant investment in research and development. Key R&D hubs in San Francisco and Seoul will see enhanced resources. This supports continuous innovation in video understanding. Geographic growth is also a priority. New offices will open in New York and London. This move meets increasing global customer demand. It solidifies TwelveLabs' international footprint.
At its core, TwelveLabs builds a revolutionary agentic intelligence system. This system is designed specifically for video. It integrates perception, knowledge, and reasoning into a single architecture. This approach deviates from conventional methods. It allows machines to genuinely perceive, understand, and reason about video content. The company aims to transform vast, previously inaccessible video archives. They become living, searchable systems.
Video represents the majority of global data. Yet, much remains opaque. Traditional language models often sample or interpret video indirectly. TwelveLabs offers a different path. Its models are purpose-built for video. They establish genuine multimodality from the ground up. This unique design grants superior video cognition.
The company's flagship models drive this innovation. Marengo 3.0 is one such foundational model. It meticulously understands every sound, word, and motion on screen. It grasps visual context across time. Marengo 3.0 converts raw video into a semantic layer. AI systems can then understand and search this data at scale.
Pegasus 1.5 complements Marengo's capabilities. Pegasus transforms video into structured data. This includes scene boundaries, entities, temporal segments, and semantic context. It functions as a domain-specific language for video understanding. Raw footage becomes parseable by any intelligent system built atop it. Together, Marengo and Pegasus form the bedrock of TwelveLabs' platform. They power advanced applications.
This architecture enables groundbreaking capabilities. TwelveLabs' agentic system creates a structured, persistent memory. It stores every ingested video. The system then reasons across this memory. Its intelligence compounds with each new piece of content. This differs starkly from tools that reset with every query. It builds cumulative knowledge.
Enterprises are embracing this shift. They move from mere experimentation to production-scale deployment. Video understanding technology becomes critical infrastructure. Use cases span multiple sectors. Media and entertainment gained early traction. The public sector now applies video intelligence to mission-critical workflows. Governments worldwide benefit.
Additional verticals drive demand. Advertising leverages insights for targeted campaigns. Security applications gain enhanced monitoring and analysis. Sports benefits from detailed player and event tracking. The automotive industry uses video intelligence for autonomous systems and safety. Each sector holds immense, untapped video data. TwelveLabs unlocks its value.
Strategic partnerships fortify TwelveLabs' position. A deepened collaboration with Amazon Web Services (AWS) is key. AWS serves as TwelveLabs' preferred cloud provider. The companies forged a multiyear commitment. This optimizes TwelveLabs' video inference workloads on AWS Trainium chips. Furthermore, new frontier models will debut first on AWS. This partnership supports scaling video cognition at production levels.
TwelveLabs also pushes into application-layer products. Rodeo launched recently. It represents the company's first such offering. This signifies a move up the stack. It empowers creators, operators, and decision-makers directly. The ultimate goal is a cohesive video intelligence platform across the full stack.
The company's vision extends far. It aims to build the intelligence layer for video. This layer will serve every user, agent, and machine needing to understand the world. The founders made a "contrarian bet" years ago. They believed recorded reality in motion, not language, was the true substrate of machine intelligence. Video holds the answers.
This funding empowers that belief. It allows TwelveLabs to transition. It moves from foundational models to a comprehensive video cognition system. Such a system becomes essential. It provides deep, contextual understanding of visual information. The future of AI relies on this capability.
TwelveLabs is defining what comes next. Its technology sets new standards for video understanding. It transforms how organizations interact with their visual data. This makes previously unmanageable video assets actionable. The path to "video superintelligence" is now clearly paved. It promises profound changes across global industries.
TwelveLabs charts a bold new course. The video intelligence company just announced a substantial $100 million Series B funding round. This capital infusion significantly accelerates its drive toward "video superintelligence." It marks a pivotal moment for AI's capability in understanding the visual world.
The investment round saw robust participation. NEA and NAVER Ventures co-led the funding. Esteemed investors like Amazon, Radical Ventures, Korea Investment Partners, Index Ventures, Quadrille Capital, and Red Bull Ventures joined. This latest round pushes TwelveLabs' total funding beyond $207 million. Such backing underscores deep confidence in the company's vision and technology.
Funds will fuel aggressive expansion. TwelveLabs plans significant investment in research and development. Key R&D hubs in San Francisco and Seoul will see enhanced resources. This supports continuous innovation in video understanding. Geographic growth is also a priority. New offices will open in New York and London. This move meets increasing global customer demand. It solidifies TwelveLabs' international footprint.
At its core, TwelveLabs builds a revolutionary agentic intelligence system. This system is designed specifically for video. It integrates perception, knowledge, and reasoning into a single architecture. This approach deviates from conventional methods. It allows machines to genuinely perceive, understand, and reason about video content. The company aims to transform vast, previously inaccessible video archives. They become living, searchable systems.
Video represents the majority of global data. Yet, much remains opaque. Traditional language models often sample or interpret video indirectly. TwelveLabs offers a different path. Its models are purpose-built for video. They establish genuine multimodality from the ground up. This unique design grants superior video cognition.
The company's flagship models drive this innovation. Marengo 3.0 is one such foundational model. It meticulously understands every sound, word, and motion on screen. It grasps visual context across time. Marengo 3.0 converts raw video into a semantic layer. AI systems can then understand and search this data at scale.
Pegasus 1.5 complements Marengo's capabilities. Pegasus transforms video into structured data. This includes scene boundaries, entities, temporal segments, and semantic context. It functions as a domain-specific language for video understanding. Raw footage becomes parseable by any intelligent system built atop it. Together, Marengo and Pegasus form the bedrock of TwelveLabs' platform. They power advanced applications.
This architecture enables groundbreaking capabilities. TwelveLabs' agentic system creates a structured, persistent memory. It stores every ingested video. The system then reasons across this memory. Its intelligence compounds with each new piece of content. This differs starkly from tools that reset with every query. It builds cumulative knowledge.
Enterprises are embracing this shift. They move from mere experimentation to production-scale deployment. Video understanding technology becomes critical infrastructure. Use cases span multiple sectors. Media and entertainment gained early traction. The public sector now applies video intelligence to mission-critical workflows. Governments worldwide benefit.
Additional verticals drive demand. Advertising leverages insights for targeted campaigns. Security applications gain enhanced monitoring and analysis. Sports benefits from detailed player and event tracking. The automotive industry uses video intelligence for autonomous systems and safety. Each sector holds immense, untapped video data. TwelveLabs unlocks its value.
Strategic partnerships fortify TwelveLabs' position. A deepened collaboration with Amazon Web Services (AWS) is key. AWS serves as TwelveLabs' preferred cloud provider. The companies forged a multiyear commitment. This optimizes TwelveLabs' video inference workloads on AWS Trainium chips. Furthermore, new frontier models will debut first on AWS. This partnership supports scaling video cognition at production levels.
TwelveLabs also pushes into application-layer products. Rodeo launched recently. It represents the company's first such offering. This signifies a move up the stack. It empowers creators, operators, and decision-makers directly. The ultimate goal is a cohesive video intelligence platform across the full stack.
The company's vision extends far. It aims to build the intelligence layer for video. This layer will serve every user, agent, and machine needing to understand the world. The founders made a "contrarian bet" years ago. They believed recorded reality in motion, not language, was the true substrate of machine intelligence. Video holds the answers.
This funding empowers that belief. It allows TwelveLabs to transition. It moves from foundational models to a comprehensive video cognition system. Such a system becomes essential. It provides deep, contextual understanding of visual information. The future of AI relies on this capability.
TwelveLabs is defining what comes next. Its technology sets new standards for video understanding. It transforms how organizations interact with their visual data. This makes previously unmanageable video assets actionable. The path to "video superintelligence" is now clearly paved. It promises profound changes across global industries.