Internal footage retrieval
Problem: Teams sit on hours of raw recordings, including sales calls, user interviews, and training sessions. Finding a specific moment means scrubbing through video manually. How Pureframe AI helps: Upload recordings to a collection and search with natural language. A query such ascustomer mentions pricing returns relevant timestamped segments without requiring users to scrub each recording.
AI agent with video context
Problem: An AI assistant needs a retrieval tool before it can answer questions about a private video library. How Pureframe AI helps: Connect the Pureframe AI MCP server or function-calling API to a compatible model. The agent can search footage and retrieve frame images and transcript passages. Design the agent to cite the supporting timestamp. See Source-backed results. Example agent prompt:"Find the part of last week's demo where we showed the pricing page, and tell me what the presenter said about the annual plan."
Video search for end users
Problem: You’re building a product that includes video content and users need to find specific moments without scrubbing. How Pureframe AI helps: Use the search API to power a search bar in your app. Users type what they’re looking for, and your UI displays the matched clips with thumbnails and timestamps. Results include presigned playback URLs ready for your video player.Content moderation at scale
Problem: You have a library of user-generated video and need to identify specific types of content (e.g., sensitive scenes, brand mentions, competitor references). How Pureframe AI helps: Run recurring searches across your library using themodes parameter (video, transcript, scene) to surface content that matches your criteria. Automate flagging and review workflows using the API.
Training data curation
Problem: You need labeled video clips for a fine-tuning or evaluation dataset, but manually reviewing hours of footage isn’t practical. How Pureframe AI helps: Describe the moments you need, such as"person looking directly at the camera", "close-up of hands on keyboard", or "outdoor scene with natural light". Then extract matched clips with timestamps. Use thumbnail_base64 to pass frames directly to a vision model for automated labeling.
Meeting and lecture search
Problem: You record meetings or lectures and want attendees to find specific topics discussed without watching the whole recording. How Pureframe AI helps: Upload recordings to a per-meeting or per-course collection. Expose a search box powered byPOST /v1/search with modes=transcript: users search what was said and jump directly to the moment in the recording.