Structured Extraction
for Videos
Automatically extract structured metadata from video—at scale.
problem
Manual Tagging Doesn’t Scale
Video metadata is often incomplete, inconsistent, or missing entirely. Manual tagging is slow, expensive, and brittle—especially as libraries grow into thousands of hours.
Our Solution
Flowstate Agents Automatically Extract Structured Metadata from Videos
Metadata Extraction automatically watches video and outputs clean, structured metadata—ready for search, analytics, compliance, and downstream workflows.
Define your taxonomy once. FlowState extracts and maintains it across your entire library.
Testimonials
Hear what our customers have to say
FAQ
What is AI video tagging?
AI video tagging uses artificial intelligence to automatically categorize video content by detecting people, objects, scenes, actions, and contextual signals within video files. Flowstate generates structured metadata that transforms raw footage into usable, searchable data.
What is video metadata extraction?
Video metadata extraction is the process of converting unstructured video into structured video data such as entities, scenes, timestamps, and topics. Flowstate automates metadata extraction at scale, helping teams organize large video libraries and operationalize video across systems.
How does Flowstate automate video tagging?
Flowstate uses an AI-powered tagging system built on advanced algorithms and multimodal AI models to analyze video content. The system auto-tags footage with consistent metadata, reducing manual effort while improving accuracy across large datasets.
Can Flowstate extract metadata from untagged video files?
Yes. Flowstate analyzes raw video files without requiring pre-existing tags or transcription. The platform automatically categorizes and structures metadata, making it ideal for legacy archives and rapidly growing content libraries.
What types of metadata can Flowstate generate?
Flowstate generates AI-generated metadata including scenes and segments, entities such as people, brands, and locations, actions and contextual signals, and timestamps for precise navigation. This structured output helps teams optimize workflows, governance, and analytics.
Can metadata be customized to our taxonomy?
Yes. Teams can define a custom video taxonomy aligned with their domain — whether for media, sports, compliance, e-commerce, or internal operations. Flowstate applies domain context during extraction to maintain consistent and auditable metadata.
Does Flowstate support human review?
Yes. Flowstate supports human-in-the-loop video tagging so teams can review, approve, or refine extracted metadata. This ensures tagging accuracy while maintaining trust in the AI system.
Can Flowstate integrate with existing platforms?
Yes. Flowstate provides a video metadata API that allows teams to integrate structured metadata into existing platforms, automation pipelines, and operational workflows.
How does automated tagging help teams use video more effectively?
Automated content tagging helps teams organize video content faster, reuse footage across projects, support social media workflows, and streamline content creation without relying on manual processes.
What AI models power Flowstate’s metadata extraction?
Flowstate uses a model-flexible architecture that evaluates and deploys the best-performing AI models for each task. By remaining model-agnostic rather than dependent on a single provider, Flowstate ensures metadata quality improves as artificial intelligence advances.
How is Structured Extraction priced?
Flowstate pricing is usage-based and depends on factors such as video volume, metadata complexity, processing requirements, and deployment preferences. Most teams begin with a guided pilot to evaluate performance before moving into production.
