VII was built because the world produces more video than humans can ever watch — but that doesn't mean it should go unwatched.
Organizations deploy thousands of cameras but only review footage reactively — after an incident, when it's already too late. The vast majority of video data is never analyzed at all.
Traditional computer vision requires per-camera calibration, custom model training, and rigid rule sets. It can detect a person crossing a line but can't tell you what happened.
Vision language models can understand scenes the way a human would — describing actions, identifying anomalies, recognizing context. VII brings this capability to continuous video streams at production scale.
The result isn't a bounding box — it's a narrative. “At 02:14, a person in a red jacket entered through the west gate carrying a large package. They were not detected in the authorized personnel database.”
Video is among the most sensitive data. VII is designed so data never has to leave your infrastructure. On-prem, air-gapped, always encrypted.
We build for developers first. Shared app SDK, UI kit, OpenAPI specs, and clear documentation. If it takes more than 10 lines to get started, we failed.
The core engine doesn't assume your industry. Security, defense, retail, healthcare — the same pipeline, different prompts and schemas. Build what you need.
Swap VLM providers. Bring your own models. Export your data freely. No lock-in, no proprietary formats, no walled gardens.
Research phase — exploring VLM capabilities for video understanding at scale.
Core engine built. First production deployment with a private security firm analyzing 200+ camera feeds.
Platform launch. Multi-tenant architecture, app marketplace, and developer SDK in early access.
Embedded app builder. Real-time streaming analysis. Edge device deployment for latency-critical use cases.