Vivu.ai

Vivu.ai is an AI search tool that makes an existing video library searchable and callable by AI agents. Vivu indexes a video library once and makes it searchable in plain language and callable from ChatGPT and Claude, using a graph of video and context nodes to answer queries.

Vivu positions itself as a video intelligence layer rather than a video editor. The product indexes a video library once, then exposes that indexed material to the AI tools a team already runs. Instead of hunting through folders and timelines by hand, users describe what they want in plain language and let a model retrieve the matching footage or segment. The homepage frames the problem bluntly: most video libraries remain dark to AI workflows, and Vivu is the connector that turns them into queryable context. The core mechanism is a graph. External context dots from multiple sources are ingested into a single network of video and context nodes, and queries converge on one answer from that network. In practice this means a clip is not just a file with a filename; it sits alongside related context, so a question like which footage covers a given topic can resolve against the graph rather than a keyword index. That design suits teams with large archives, marketing and media groups with years of B-roll, and research or editorial operations that need to find specific moments quickly. Distribution is the notable choice. Vivu is reached through ChatGPT and Claude rather than only through a standalone interface, so the retrieval step happens inside a conversation the user is already having. That lowers setup friction for anyone already working in those assistants, and it means the video layer follows the agent rather than competing with it. Against conventional video editing software, Vivu is complementary. It does not appear to offer cutting, grading or timeline tools; it offers discovery and context. Buyers should treat it as infrastructure for finding and feeding footage into other workflows, not as a replacement for an NLE. Pricing, storage limits and supported source connectors are not stated on the homepage, so those details need confirmation before a rollout decision.