Twelve Labs

Twelve Labs is a video intelligence platform for searching and analyzing video and generating embeddings for machine-learning pipelines. Its Search capability locates moments through natural-language queries spanning speech, text, audio and visuals. The platform can also summarize a video or answer prompts about it. Jockey is a research-preview agent that can reason across videos and images and return answers with cited moments. Developers can use REST APIs and Python or Node.js SDKs; models are also available through Amazon Bedrock and AWS Marketplace. The Free plan includes 600 minutes of video usage, with indexes accessible for 90 days after creation, up to 10 hours and 100 videos per index, and five concurrent indexing tasks. The Developer plan is pay as you go: listed charges are $2.50 per hour for indexing, $0.09 per hour per month for infrastructure, and $4 per 1,000 search queries. Enterprise options describe deployment in cloud, private cloud or on-premises environments. Twelve Labs states that data in transit is protected with TLS 1.2 or higher and stored data with at least AES 256-bit encryption.

Twelve Labs provides video search, analysis and embeddings through APIs and SDKs. The Free plan has usage and index-duration limits, while Developer usage is pay as you go.

It suits developers and teams building video search, analysis or machine-learning workflows. The listed deployment choices also address enterprise environments.

Twelve Labs is a developer-focused video intelligence platform for searching, analyzing, and embedding video. It suits teams building video products, machine-learning pipelines, or enterprise media workflows that need programmable access. Its strongest advantage is multimodal understanding; the main caution is that retention and usage costs become material as projects grow.

Overview

Natural-language queries can locate moments through speech, on-screen text, audio, and visual content, so searches are not limited to transcript keywords. Analysis can generate summaries or answer prompts about a video, while vector embeddings can feed a team’s own machine-learning pipeline. That combination is more useful for applications and internal systems than for casual personal media browsing.

REST APIs plus Python and Node.js SDKs provide conventional integration paths. Twelve Labs models are also offered through Amazon Bedrock and AWS Marketplace, which may fit organizations already operating in AWS. Data in transit is protected with TLS 1.2 or higher, and stored data uses at least AES 256-bit encryption. The Trust Center lists SOC 2 Type II reports for 2024 and 2025 and TPN Verified status. Enterprise deployments can run in cloud, private-cloud, or on-premises environments.

Key features

• Multimodal search: Queries span speech, text, audio, and visuals. This is valuable when the sought moment is shown or heard rather than explicitly spoken, and it avoids building separate search paths for each medium.
• Video analysis: The platform returns summaries or answers to prompts. It is suited to extracting usable information from long recordings, though teams should still design their applications around the quality and consistency they require from generated answers.
• Embeddings: Video-derived vector embeddings can be incorporated into machine-learning pipelines, giving engineering teams a way to combine Twelve Labs’ video representation with their own systems.
• Jockey agent: This research-preview agent reasons across videos and images and returns answers with cited moments. The citations can make results easier to inspect, but its preview status makes it less appropriate as the sole foundation for a critical workflow.
• Developer access: REST, Python, and Node.js interfaces support application development rather than restricting use to a web interface.
• AWS availability: Bedrock and AWS Marketplace access can simplify adoption for AWS-centered organizations.

Pricing

The Free plan costs $0, billed Free. It includes 600 minutes of video usage, 90-day index access, a 10-hour maximum per index, 100 videos per index, and five concurrent indexing tasks. This is enough for prototyping and small evaluations, but the 90-day access window means it is not a permanent archive.

Developer pricing is pay as you go, with rates varying by API usage. It provides unlimited video hours and unlimited index access, supports up to 10,000 hours and 100,000 videos per index, and allows 25 concurrent indexing tasks. Published rates are indexing at $2.50/hour, infrastructure at $0.09/hour/month, and search at $4/1,000 queries. That flexibility fits variable workloads, but costs track both ingestion and ongoing infrastructure, so high-volume or heavily queried services need budgeting.

Enterprise uses committed use contracts with custom pricing. It offers unlimited indexing hours plus custom pricing and limits, including custom index duration, volume, and concurrent indexing tasks. This is the appropriate tier when retention, scale, deployment model, or contractual requirements exceed the fixed Free and Developer boundaries.

Platforms

Twelve Labs supports API and web access. Developers can integrate through REST, Python, or Node.js, while enterprise customers can choose cloud, private-cloud, or on-premises deployment. Assistance is available through [email protected].

Who it's for

Choose Twelve Labs if you are building a video search feature, an analysis workflow, or a machine-learning system that needs multimodal video understanding and embeddings. It is also a strong candidate for organizations that need AWS distribution or enterprise deployment choices. It is less suitable for a simple personal video catalog, a fixed-price service requirement, or workloads that cannot accommodate expiring free indexes and metered usage.

Pros and cons

Pros

• Search covers speech, text, audio, and visuals, enabling genuinely multimodal discovery.
• Embeddings, APIs, and SDKs support integration into custom products and machine-learning pipelines.
• Enterprise options include private-cloud and on-premises deployment, with documented encryption and compliance credentials.
• The Free plan offers 600 minutes and five concurrent indexing tasks without a charge, making initial prototyping practical.

Cons

• Free indexes remain accessible for only 90 days, limiting long-term use on the no-cost tier.
• Developer billing separates indexing, infrastructure, and search, which can make costs rise with both corpus size and query volume.
• Jockey is a research preview, so it should not be treated as a mature replacement for a production-critical process.

Alternatives

FrameQuery is a better fit for desktop-oriented teams needing local, Drive, or NAS sharing and backup; its free plan has no monthly indexing hours, while face, voice, and AI-tag search require indexed video.

DISKO suits Mac and web users seeking screenwriting and shot-list tools, review links, and a 2 GB free cloud tier rather than an API-first video intelligence platform.

QMedia is the straightforward choice when free, MIT-licensed, self-hosted software matters more than a managed multimodal service.

ViSearch fits smaller experiments that need a no-card 20-minute free allowance and per-minute processing, with a Basic plan at $0.09 per minute.

Vivu is aimed at web-based personal workspaces, offering 20 indexing minutes and 50 search credits per month on its free plan.

Cinestar is a free Linux and macOS option centered on an open-source core and local AI services through Ollama.

Moment Search is preferable for on-device Mac or Windows searching of one footage source and up to 25 indexed videos.

Scout Suite is an open-source, self-hosted multi-cloud security auditing tool rather than a video intelligence platform.

For a broader comparison, see AI Video Search Tools.

Verdict

Twelve Labs is a strong choice for developers and enterprises that need multimodal video search, analysis, and embeddings behind an API, especially with AWS or flexible deployment requirements. Look elsewhere if you need predictable flat pricing, permanent free-tier retention, or a simple consumer-facing media organizer.