Twelve Labs
6
📝 Overview
- Replace manual video tagging with instant semantic search across your entire catalog using multimodal AI that extracts actions, objects, text, speech, and people
- Automate content moderation and brand safety compliance by instantly detecting safety violations within video content using contextual understanding
- Find specific evidence moments in CCTV and surveillance footage through natural language queries instead of scrubbing timelines
- Deliver precise video recommendations and contextual advertising by understanding actual video content rather than relying on metadata
- Create custom video AI models for domain-specific needs with minimal training data using fine-tuning capabilities on top of state-of-the-art video understanding
- Integrate advanced video intelligence into applications within hours using simple two-step API process (index then search) with minimal code
⚖️ Pros & Cons
Pros
- Extracts key features from videos
- Transforms information into vector representations
- Fast and scalable semantic search
- Outperforms open-source and commercial models
- Won #1 in ICCV VALUE Challenge
- Customizable platform
- Easy API integration
- Rich understanding of video content
- Used for multiple applications
- Effective for contextual advertising
- Enables content moderation
- Efficient in evidence search
- Improves content search
- Enhances media analytics
- Assists in digital asset management
- Ensures brand safety
- Simplifies lecture search
- Smoothens video recommendation
- Assists in video editing
- Search any visuals, conversations, logos, text
- End-to-end infrastructure
- State-of-the-art accuracy
- Two-step (Index - Search) process
- Supports multiple outputs, minimal training
- Easy deployment
- APIs and playground for developers
- Transforms video into a vector embedding
- Offers fine-tuned models
- Used for locating ad insertion points
- Efficient in identifying safety violations
- Search precise moments within CCTV footage
Cons
- Lack of pricing information
- No download option
- No offline capabilities
- Requires technical knowledge
- Customization may take time
- Limited documentation
- Doesn't support all languages
- May miss nuanced context
- No distributed search option
- No mobile app
❓ Frequently Asked Questions
Twelve Labs' main function is to provide an AI-driven video search platform. This platform assists developers in creating applications capable of understanding the world, comparable to human capabilities, via its potent video search API.
What distinguishes Twelve Labs from other AI tools is its superior performance and fine-tunable nature. It has led fields like video retrieval in competitions like the 2021 ICCV VALUE Challenge hosted by Microsoft. Customizability is also a crucial aspect, with the platform offering multimodal contextual understanding and easy integration that fits various applications.
Twelve Labs extracts key features from videos such as action, objects, text on screen, speech, and people. This extensive and comprehensive feature extraction capability contributes to its sophisticated video understanding.
At Twelve Labs, the vector representations function works by transforming the extracted information like action, objects, text on screen, speech, and people into vector representations. These vectors expedite and scale semantic search, providing a deeper understanding of video content.
Twelve Labs is highly customizable to satisfy specific needs. It provides multimodal contextual understanding and enables easy integration with just a few API calls. Furthermore, developers can fine-tune their models on top of Twelve Labs' state-of-the-art video understanding AI for domain-specific needs.
Twelve Labs is used in a variety of applications, such as contextual advertising, content moderation, evidence search, content search, media analytics, digital asset management, brand safety, lecture search, video recommendation, and video editing.
Yes, Twelve Labs provides a suite of APIs for developers. It allows them to make their video catalogs searchable, transform their videos into vector embeddings, and create customized models for their domain-specific needs.
Twelve Labs can be used by developers and product managers looking to build applications with a rich understanding of video content.
The potential use cases for Twelve Labs are vast. It can be utilized for contextual advertising, automating content moderation and brand safety analytics, conducting evidence search in CCTV and camera footage, enhancing content search in video products, performing media analytics, managing digital assets, ensuring brand safety, searching lectures, making video recommendations, and editing videos.
Twelve Labs' AI models outperform open-source and commercial models. They deliver context-specific search and insights, replacing ineffective keyword tagging. This assertion is backed by their top rank in the video retrieval track from the 2021 ICCV VALUE Challenge hosted by Microsoft.
Twelve Labs can optimize for a variety of needs, ranging from making a video catalog searchable to customizing models for domain-specific needs. This flexibility is a crucial aspect of Twelve Labs, making it adaptable to various applications.
Twelve Labs provides an intuitive and easy experience for developers. It offers a 2-step process (Index - Search) to make the entire video catalog searchable. Developers can rapidly implement the AI capabilities of Twelve Labs with just a few API calls, emphasizing ease of integration.
Twelve Labs' superior performance in the video retrieval track is due to its comprehensive AI that extracts key features from video and transforms that information into vector representations. This enables fast and scalable semantic search, marking Twelve Labs as a top performer in video understanding and retrieval.
Yes, Twelve Labs can be integrated with other platforms or tools. The platform provides APIs that developers can quickly incorporate into their applications with only a few calls.
Oracle is one of the partners of Twelve Labs, as inferred from their recent partnership aimed at bringing video understanding to the market.
The integration of Twelve Labs' video understanding AI is a simple two-step process. Firstly, you index your video into the platform, and secondly, you employ the system to search through your catalog. These steps make your entire video catalog searchable.
Twelve Labs turns a video catalog searchable through its advanced AI algorithms that extract key features from the videos and transform them into vector representations. This function manipulates the semantic features of the video, thereby allowing quick and effective search functionality.
Developers can adjust Twelve Labs to their domain-specific needs by fine-tuning their own models on top of Twelve Labs' state-of-the-art video understanding AI. The platform supports multiple outputs, minimal training, and easy deployment, adjusting to specific domain needs.
Yes, users can fine-tune models using Twelve Labs' platform. They can create a customized model for their domain-specific needs, on top of Twelve Labs' state-of-the-art video understanding AI.
Twelve Labs plays a pivotal role in content moderation by automating the process. Its AI can quickly and accurately identify safety violations within video, which helps maintain brand safety and facilitates content moderation.
Yes, Twelve Labs provides a suite of APIs for developers. It allows them to make their video catalogs searchable, transform their videos into vector embeddings, and create customized models for their domain-specific needs.
Twelve Labs can be used by developers and product managers looking to build applications with a rich understanding of video content.
The potential use cases for Twelve Labs are vast. It can be utilized for contextual advertising, automating content moderation and brand safety analytics, conducting evidence search in CCTV and camera footage, enhancing content search in video products, performing media analytics, managing digital assets, ensuring brand safety, searching lectures, making video recommendations, and editing videos.
Twelve Labs' AI models outperform open-source and commercial models. They deliver context-specific search and insights, replacing ineffective keyword tagging. This assertion is backed by their top rank in the video retrieval track from the 2021 ICCV VALUE Challenge hosted by Microsoft.
Twelve Labs can optimize for a variety of needs, ranging from making a video catalog searchable to customizing models for domain-specific needs. This flexibility is a crucial aspect of Twelve Labs, making it adaptable to various applications.
Twelve Labs provides an intuitive and easy experience for developers. It offers a 2-step process (Index - Search) to make the entire video catalog searchable. Developers can rapidly implement the AI capabilities of Twelve Labs with just a few API calls, emphasizing ease of integration.
Twelve Labs' superior performance in the video retrieval track is due to its comprehensive AI that extracts key features from video and transforms that information into vector representations. This enables fast and scalable semantic search, marking Twelve Labs as a top performer in video understanding and retrieval.
Yes, Twelve Labs can be integrated with other platforms or tools. The platform provides APIs that developers can quickly incorporate into their applications with only a few calls.
Oracle is one of the partners of Twelve Labs, as inferred from their recent partnership aimed at bringing video understanding to the market.
The integration of Twelve Labs' video understanding AI is a simple two-step process. Firstly, you index your video into the platform, and secondly, you employ the system to search through your catalog. These steps make your entire video catalog searchable.
Twelve Labs turns a video catalog searchable through its advanced AI algorithms that extract key features from the videos and transform them into vector representations. This function manipulates the semantic features of the video, thereby allowing quick and effective search functionality.
Developers can adjust Twelve Labs to their domain-specific needs by fine-tuning their own models on top of Twelve Labs' state-of-the-art video understanding AI. The platform supports multiple outputs, minimal training, and easy deployment, adjusting to specific domain needs.
Yes, users can fine-tune models using Twelve Labs' platform. They can create a customized model for their domain-specific needs, on top of Twelve Labs' state-of-the-art video understanding AI.
Twelve Labs plays a pivotal role in content moderation by automating the process. Its AI can quickly and accurately identify safety violations within video, which helps maintain brand safety and facilitates content moderation.
💰 Pricing
Pricing model
Freemium
Paid options from
$0.10/month
Billing frequency
Monthly
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