Quick Keypoints
- Extracts schema-aware metadata and incidents from video libraries.
- Indexes video, audio, and images into high-dimensional search vectors.
- Implements agentic MediaRAG to preserve cross-asset media context.
- Provides developer-first APIs and webhooks for pipeline automation.
What is VideoVector?
Enterprise AI media intelligence and multimodal search API.
VideoVector is an enterprise-grade media intelligence and search API built by VectorMethods. It processes unstructured video, audio, and images into searchable vector embeddings, enabling developers to integrate semantic search, visual lookup, and automated schema-aware JSON metadata extraction into their products.
Who Needs VideoVector?
Software developers, newsroom operators, compliance managers, and digital archive managers.
Primary Use Cases
- Searching massive video archives by spoken phrases or visual entities.
- Automating incident reporting and compliance tracking from security feeds.
- Building AI-driven search and clip recommendation engines for publishers.
Important Features
- Multimodal Search: Search media libraries using text, images, or custom filters.
- MediaRAG: Advanced retrieval-augmented generation built specifically for video files.
- Schema-aware JSON: Extract structured fields from raw files using natural language prompts.
Current Updates About VideoVector
- Added version tracking for extraction engines and schema iterations to compare outputs from different runs.
- Current Version: v1.0
Alternatives to VideoVector
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Pricing Plans
| Plan | Price |
|---|---|
| FreeTrial search functionality, extraction testing, and schema design. | $0 |
| Self-ServeFlexible usage pricing based on processing credits for growing workloads. | Custom |
| EnterpriseTailored processing credits, custom workflows, and private cloud deployment. | Custom |
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