Turn massive video libraries into searchable intelligence.
Show every moment a forklift came within two metres 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, behaviours, and evidence spread across thousands. GVTLabs is built for that.
Agentic orchestration. Multimodal preprocessing. Temporal understanding. Together they 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 corpora. 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 specialist signals: transcript, visual narrative, motion, objects, people, scenes, timing, and domain-specific analysis. Then recombine them per question.
That means enterprise customers can tune what the system attends to: 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 compounds. The latency compounds. The carbon compounds.
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.
Indicative · workload-dependentThe platform is sector-agnostic. The detector stack is tunable. Below are the patterns we see most often. But if your team already has a question, the answer is probably already in your footage.
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.
Measure brand presence across creator video, broadcast, in-store cameras. Quantify what no panel survey can.
An agent that follows evidence across thousands of clips, returns sourced moments, and explains the reasoning trail.
Index surgical phases, instruments, hand-offs, anomalies. Compare cases. Review the moment, not the file.
AskGVT is the world's first visual intelligence answer engine. A consumer surface built on the same multimodal index, agentic stack, and temporal layer described above. It's how we prove the platform works at internet scale, and it's the front door for creators and consumers today.
The enterprise platform is what the question demands. The same intelligence, wired into your systems, tuned to your domain.
We work with a small number of enterprise design partners while the platform is in preview. If your team has a question that lives in video, we'd like to hear it.