TwelveLabs
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Tool Introduction:Multimodal video AI for deep search, analytics, and workflow automation.
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Inclusion Date:Nov 07, 2025
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Tool Information
What is TwelveLabs AI
TwelveLabs AI is a video intelligence platform powered by multimodal foundation models like Marengo and Pegasus. It understands vision, audio, speech, and on‑screen text to index large video libraries, enabling semantic video search, deep analysis, and video‑to‑text generation at scale. With natural language queries, users can find scenes, actions, objects, and topics, then extract summaries, captions, and time‑coded insights. Delivered via API and tools, TwelveLabs helps teams automate video workflows, enrich metadata, and accelerate content discovery.
Main Features of TwelveLabs AI
- Multimodal video understanding: Combines visual signals, audio, ASR, and OCR to interpret context, actions, and entities within long-form video.
- Semantic video search: Natural language search across massive archives with temporal localization to jump to the exact moment in a timeline.
- Video indexing and embeddings: Generates high-quality video embeddings for fast retrieval, tagging, and similarity search.
- Video-to-text generation: Automated summaries, captions, and descriptions to power SEO, archives, and accessibility.
- Action, object, and scene detection: Identify concepts, topics, and shot changes for detailed metadata enrichment.
- Scalable API and SDKs: Process large volumes with batch ingestion, webhooks, and developer-friendly endpoints.
- Customization options: Tune search behavior and indexing strategies to match domain-specific content and taxonomies.
- Analytics and workflow automation: Build pipelines that discover highlights, flag sensitive content, and automate review.
- Enterprise readiness: Privacy controls and integrations with MAM/DAM and cloud storage for production deployments.
- Benchmarked accuracy: Published benchmarks indicate competitive performance versus major cloud and open-source models.
Who Can Use TwelveLabs AI
TwelveLabs AI suits media and entertainment teams, sports broadcasters, newsrooms, and streaming services that need fast content discovery. Marketers and social teams can auto-generate captions, summaries, and video chapters to improve engagement and video SEO. Educators, e-learning platforms, and knowledge managers can index lectures and training videos for search. Developers and product teams can embed video search and analytics into apps, while compliance and trust & safety teams automate content review.
How to Use TwelveLabs AI
- Connect storage or upload: Link cloud buckets or upload files via the API or tools.
- Choose a model and settings: Select Marengo/Pegasus, set languages, indexing cadence, and metadata options.
- Ingest and index: The platform creates video embeddings, transcripts, OCR, and time-coded metadata.
- Query with natural language: Search for scenes, actions, objects, people, or topics; filter by time ranges and confidence.
- Generate outputs: Produce summaries, captions, and highlights; export JSON, SRT, or structured metadata to your systems.
- Automate workflows: Use webhooks and SDKs to trigger reviews, clip creation, or downstream analytics at scale.
TwelveLabs AI Use Cases
Media archives use TwelveLabs to surface relevant clips for editorial and licensing. Sports organizations detect key plays and auto-generate highlight reels. Advertisers and agencies perform contextual targeting and brand safety checks. Streaming services enable personalized discovery and chaptering. Learning platforms index lectures for question answering and semantic search. Enterprises apply content moderation, compliance review, and knowledge retrieval across training and town halls.
TwelveLabs AI Pricing
TwelveLabs typically offers usage-based API billing aligned to processing volume and feature access, with custom enterprise agreements for higher throughput and advanced controls. Organizations can engage sales for tailored plans, volume discounts, and evaluation options suited to their scale and security requirements.
Pros and Cons of TwelveLabs AI
Pros:
- Accurate multimodal understanding across vision, audio, ASR, and OCR.
- Natural language, time-coded semantic video search over large libraries.
- Scales to enterprise workloads via robust API and batch processing.
- Rich metadata and embeddings enable powerful retrieval and analytics.
- Customization options to match domain-specific taxonomies and use cases.
Cons:
- High-volume processing can incur significant compute and storage costs.
- Fine-tuning and taxonomy design may require ML and IR expertise.
- Requires careful handling of sensitive video content and access controls.
- Ingestion of large archives depends on network bandwidth and egress policies.
FAQs about TwelveLabs AI
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Does TwelveLabs support long-form videos?
Yes. Its indexing and embeddings are built for long-form content, returning time-coded results for precise navigation.
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Can I search videos with natural language?
Yes. You can query using plain English to find actions, objects, topics, and moments without manual tagging.
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Is near real-time processing available?
The platform is optimized for at-scale processing of recorded video, with workflows that can be tuned for low-latency needs.
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How is TwelveLabs different from basic transcription tools?
It goes beyond ASR by combining visual, audio, and text cues to understand scenes, actions, and context for richer search and analysis.