Smart Search for Videos
Turn raw videos into a searchable system.
Video doesn’t behave like text
As video libraries grow into hundreds or thousands of hours, discovery breaks down. Finding a specific moment still requires manual scrubbing, filenames, or tribal knowledge—especially when footage was never tagged correctly.
Flowstate Makes Videos Searchable
Smart Search turns raw video into a searchable system. Ask questions in natural language and instantly retrieve the exact moments—across archives, new uploads, and enterprise workflows.
Testimonials
Hear what our customers have to say
FAQ
What is AI video search?
AI video search allows teams to search inside video content using natural language instead of relying on filenames or manual tags. Flowstate analyzes video data to retrieve relevant moments with precise timestamps — turning raw footage into a searchable system.
How does Flowstate understand video content?
Flowstate uses multimodal video analysis to interpret speech, visuals, motion, and contextual signals within video files. This semantic approach helps teams locate scenes, actions, and moments with greater accuracy — even in untagged or legacy video.
What does semantic video search mean?
Semantic video search allows teams to search by meaning rather than exact words. Flowstate understands intent, context, and visual cues so queries return relevant moments — even if the exact terms were never spoken.
Does Flowstate work on untagged or legacy videos?
Yes. Flowstate can search untagged video without requiring pre-existing metadata, making it effective for large video libraries and archival footage.
Can AI video search find specific scenes, people, or actions?
Yes. Flowstate retrieves moments based on actions, scenes, people, or visual descriptions — allowing teams to jump directly to the exact moment in video instead of manually scrubbing through files.
How accurate are the results?
Results are timestamped, transparent, and reviewable so teams can validate outputs before taking action — supporting workflows where accuracy and accountability matter. Flowstate continuously improves through system optimization and guided human feedback, helping maintain strong retrieval quality as video libraries scale.
How long does it take to index large video libraries?
Indexing is typically completed in a fraction of total video runtime. Flowstate uses parallel processing to analyze multiple video files simultaneously, significantly reducing time-to-searchability for large libraries. This architecture allows teams to begin discovering value from their video content quickly without disrupting existing workflows.
What AI models power Flowstate?
Flowstate uses a model-flexible architecture that enables the platform to evaluate and deploy the best-performing vision-language models for each task. By remaining model-agnostic rather than dependent on a single provider, Flowstate improves retrieval quality while ensuring video intelligence capabilities evolve as AI technology advances.
Can Flowstate integrate with existing systems?
Yes. Flowstate is available through a secure UI and APIs, allowing teams to embed AI video search into existing platforms, repositories, and workflows.
Who is Flowstate built for?
Flowstate is designed for organizations that manage large volumes of video and need fast, reliable discovery across archives, operational footage, training content, or media libraries.
Can Flowstate help video editors find the right footage?
Yes. Flowstate helps video editors quickly locate specific moments, reducing time spent scrubbing through footage and streamlining editing workflows.
How is Flowstate priced?
Flowstate pricing is usage-based and tailored to organizational needs. Pricing typically depends on video volume, archive size, processing requirements, and deployment preferences. Most teams begin with a guided demo or pilot to evaluate performance before moving into production.
How is Flowstate different from traditional video search tools?
Traditional video search relies heavily on manual tagging and metadata. Flowstate analyzes video directly using AI, enabling teams to retrieve moments based on meaning, context, and visual understanding — even when metadata is incomplete or missing.
