Turn massive video libraries into searchable intelligence.
Show every moment a forklift came within two meters of a pedestrian, last 90 days.
Foundation models can describe a single video. That's useful, and it's not enough. Enterprise questions are almost never about one file. They're about patterns, events, behaviors, and evidence spread across thousands. GVTLabs is built for that.
Turn video libraries into an operational intelligence layer, not another archive.
Most tools take a question and a video and give you an answer. That works for one file. It breaks the moment your question is "across all of them."
GVTLabs deploys agents that scan, inspect, compare and follow evidence across entire video libraries. Think of an analyst working through microfiche. Except the analyst is reading thousands of hours at once, refining the search on each pass, and returning the six clips that actually matter.
"What's in this video" is the easy question. "Find when X happens, then Y happens a minute later, across 100 videos" is the one enterprises actually have.
We convert every asset into structured timelines of visual, audio, motion, transcript, object, scene, and narrative signals. Agents reason over what happened, when it happened, and what happened next, within a video and across many.
We extract one signal per modality: transcript, visual narrative, motion, objects, people, scenes, timing, and domain-specific analysis. Then recombine them per question.
Tune what the system sees: brand presence, crowd size, player movement, safety incidents, gestures, scenes, actions, sequencing. Without retraining a foundation model.
Running a foundation model over a two-hour video every time you ask a question does not scale. The bill stacks up. The wait drags. The carbon emissions balloon.
GVTLabs preprocesses each video into a reusable intelligence layer. The first pass is the expensive one. After that, every additional question runs against the index. Dramatically faster, dramatically cheaper, and just as accurate.
Find every shot of a guest, every appearance of a sponsor, every recurring segment, across an entire library that was effectively dark.
Track player movement, set-piece outcomes, formation shifts. Cross-reference video with telemetry without humans tagging frames.
Surface near-misses, protocol breaks, equipment patterns, across every camera, every shift, every site. Without watching the footage.
Count every appearance, every second of screen time, every adjacency with talent or competitor. Without panel surveys, without manual review.
An agent that follows evidence across thousands of clips. Refines its search on each pass, returns timestamped citations, and shows the reasoning behind every find.
Index surgical phases, instruments, and hand-offs across every recorded procedure. Compare cases against the cohort. Review the moment, not the file.
AskGVT is the world's first in-video answer engine, powered by creators.
A consumer product built on the same multimodal index, agentic runtime, and temporal layer. It's how we prove the platform works at internet scale, and how creators and consumers meet it today.
GVTLabs is the same intelligence, running over your own video. Built around your team's questions.
We work with a small number of enterprise partners while the platform is in preview. If your team has a question that lives in video, we'd like to hear it.