Overview
Twelve Labs is a pioneering AI company specializing in advanced video understanding technology. Their innovative approach brings human-like comprehension to video analysis, offering a range of powerful capabilities and applications.
Core Technology
Twelve Labs develops sophisticated AI models that can analyze and interpret videos with a level of understanding comparable to human cognition. These models are trained to map text to various elements within videos, including actions, objects, and audio content.
Key Features
- Video Search: Users can search through videos for specific moments, generate summaries, or ask detailed questions about the content.
- Customization: Unlike general-purpose multimodal models, Twelve Labs' solutions are optimized specifically for video analysis and can be customized using clients' proprietary data.
- Multimodal Embeddings: The company's Embed API creates multimodal embeddings for videos, text, images, and audio files, capturing complex relationships between different data points.
Products and Services
- Marengo Model: A versatile model capable of searching across images, audio, and video, accepting various reference inputs to guide searches.
- API Integration: Twelve Labs provides APIs that seamlessly integrate with existing data pipelines, as demonstrated by partnerships with Databricks and Snowflake.
Applications
Twelve Labs' technology finds applications across various sectors:
- Media and Entertainment: Content moderation, ad insertion, and auto-generation of highlight reels.
- Enterprise: Real-time threat detection and enhanced data analysis.
- Public Sector: Improving emergency response times and traffic management for municipalities.
Funding and Growth
Twelve Labs has secured $107.1 million in total funding, including a recent $30 million investment from prominent backers such as Nvidia, Samsung, Intel, and Snowflake. This financial support fuels product development and talent acquisition.
Leadership
Led by co-founder and CEO Jae Lee, Twelve Labs has recently expanded its leadership team with the appointment of Yoon Kim as President and Chief Strategy Officer. This strategic move aims to drive future growth, facilitate key acquisitions, and expand the company's global presence.
Leadership Team
Twelve Labs boasts a strong leadership team driving the company's innovation in video understanding AI. Here are the key members:
Founders
- Jae Lee: Co-founder and CEO, responsible for overall strategy and growth.
- Aiden Lee: Co-founder and CTO, focusing on technical development of AI solutions.
- Dave Jinwoo Chung: Co-founder, contributing to technological and operational strategies.
- Soyoung Lee: Co-founder and Head of Business Development, driving business growth and partnerships.
Key Executive
- Dr. Yoon Kim: President and Chief Strategy Officer. Formerly CTO of SK Telecom and a key figure in developing Apple's Siri, Dr. Kim joined to spearhead future growth, expand global presence, and secure top AI talent. He divides his time between the San Francisco and Seoul offices. The leadership team is supported by additional executives and team members working on various aspects of the business, including talent acquisition, engineering, and operations. Their collective efforts are focused on enhancing Twelve Labs' video-understanding infrastructure and market impact. This diverse and experienced leadership team positions Twelve Labs at the forefront of AI-driven video understanding technology, driving innovation and growth in this rapidly evolving field.
History
Twelve Labs, a leader in video understanding and search technology, has a brief but impactful history marked by rapid growth and innovation.
Founding and Mission
- Founded in 2021 by a team of machine learning engineers in San Francisco, with an additional office in Seoul.
- Driven by the mission to contribute to human-AI symbiosis through advanced video understanding technology.
Key Milestones
- 2022: Won first place in the ICCV VALUE Challenge - Video Retrieval Track, outperforming major tech companies.
- March 2022: Launched a cloud-native suite of APIs for comprehensive video search in under one second.
- October 2023: Commercially released video-to-text generative APIs powered by the Pegasus-1 video-language foundation model.
Funding and Investments
- 2022: Secured $5 million in seed funding led by Index Ventures, with participation from notable investors including Dr. Fei-Fei Li and Alexandr Wang.
- October 2023: Received a $10 million strategic investment from Intel Capital, NVentures, Samsung Next, and others.
Technology and Impact
Twelve Labs' technology is built on advanced computer vision and natural language processing. Their multimodal AI models can:
- Map visual and audio content to language
- Extract topics from videos
- Create summaries and chapters
- Generate custom reports This technology is poised to revolutionize video content access, consumption, and utilization across various applications. In its short history, Twelve Labs has quickly established itself as a pioneer in video understanding and search, with significant achievements and rapid growth. The company's innovative approach and strong financial backing position it for continued success in the evolving AI landscape.
Products & Solutions
Twelve Labs specializes in developing advanced multimodal AI models and solutions for video content analysis. Their key offerings include:
Multimodal Foundation Models
- Marengo: A model that natively understands video content, identifying and interpreting movements, actions, objects, individuals, sounds, on-screen text, and spoken words with high accuracy. It enables high-precision semantic search, scene detection, and logical breakpoint designation.
- Pegasus: This model supports video-to-text generation, enabling deep analyses, video-specific Q&A, and highlight generation. It serves as a platform for next-gen applications such as content moderation and ad insertions.
Video Understanding Platform
The platform uses AI to extract visual, audio, textual, and contextual data from videos, offering:
- Semantic Search: Users can find exact moments within videos using natural language queries, without tags or metadata.
- Video Summarization: Generation of concise video content summaries.
- Content Analysis: Detailed insights from video data, including action, object, and sound identification.
API and Integrations
- Embed API: Creates multimodal embeddings for videos, text, images, and audio files, capturing meaning and relationships between data points.
- Integration with Snowflake and Databricks: Allows users to leverage Twelve Labs' models within existing data management and analytics workflows.
Use Cases
Twelve Labs' solutions cater to various industries:
- Media and Entertainment: Content analysis, video search, personalization, and creative versioning.
- Sports Organizations: Monetizing video archives, generating highlights, and enhancing fan engagement.
- Advertising Agencies: Ad insertion, content moderation, and targeted content generation.
- Enterprise and Public Sector: Real-time threat detection, emergency response enhancement, and traffic management.
Customization and Scalability
Twelve Labs' models are highly customizable and scalable, handling thousands of concurrent requests and processing large volumes of video data efficiently. Overall, Twelve Labs' products and solutions aim to unlock the full potential of video content, making it searchable, analyzable, and actionable at scale.
Core Technology
Twelve Labs' core technology centers on advanced multimodal AI designed for human-like comprehension of video content. Key aspects include:
Multimodal AI for Video Understanding
Twelve Labs integrates visual, audio, textual, and contextual data for holistic video content analysis, capturing complex interactions between visual cues, body language, speech, and overall context.
Foundation Models
Proprietary models like Marengo and Pegasus create rich video embeddings powering various tasks such as search, generation, and classification of video content.
Key Features
- Search: Enables precise semantic search within vast video libraries using natural language queries.
- Generate: Produces accurate text summaries, detailed reports, catchy titles, or chapter breakdowns from videos.
- Classify: Automatically categorizes videos based on relevant business criteria without custom classifiers.
Customization and Scalability
Models can be fine-tuned for specific content and domains, meeting unique industry needs. The technology is highly scalable, capable of handling terabytes or petabytes of video data.
Integration with Leading Platforms
Twelve Labs has integrated its technology with major data platforms like AWS, Snowflake, and Databricks, enabling advanced video analytics and AI-driven applications within existing data ecosystems.
Security
The company emphasizes enterprise-grade security, having completed a SOC 2 Type 2 audit to ensure data privacy and security.
Applications
The technology has diverse applications, including:
- Enhancing user experiences on content platforms
- Automating video categorization for media companies
- Extracting valuable insights from video data for business intelligence
- Supporting personalized training programs for athletes
- Creating tailored highlight reels Twelve Labs' core technology aims to transform video content into a rich, actionable data source across various industries and use cases.
Industry Peers
Twelve Labs operates in the video analytics and AI-powered video intelligence sector. Its industry peers can be categorized as follows:
Video Analytics Competitors
- Mux.com: Holding a significant market share of 75.25%
- Conviva: With a market share of 6.61%
- Bitmovin: Commanding a 6.29% market share
- Others: Circana, Scylla, and Visible Measures
AI and Multimodal Search Competitors
- Vectara: Specializing in retrieval augmented generation
- Netra: Focused on content comprehension and safety/context detection
- Neeva: Operating a private search engine using artificial intelligence
- You.com: Offering a private search engine with extensible applications and personalized results
- Sensifai: Specializing in artificial intelligence for video understanding and image recognition
- Valossa: Focused on video recognition and content intelligence
Other Relevant Competitors
- Minute: Focused on video optimization technology
- Dataperformers: Offering searchable video content recognition
- Andi: Providing a generative AI-powered search platform
- Zensors: Specializing in spatial intelligence and AI for physical space monitoring These companies compete with Twelve Labs in various aspects of video analytics, AI-powered search, and multimodal intelligence. The competitive landscape highlights the growing importance of AI-driven solutions in understanding and leveraging video content across different industries and applications. While Twelve Labs distinguishes itself through its advanced multimodal AI models and comprehensive video understanding platform, it faces strong competition from established players and innovative startups alike. This competitive environment drives continuous innovation and improvement in the field of AI-powered video analytics and intelligence.