Two products, different kinds of work
Introducing Geye and Gnome: two ways to bring useful context to everyday work. Geye explores what camera activity can tell a team about a physical space. Gnome brings AI teammates together for digital tasks. The starting point is not automation for its own sake, but a clear task and a person responsible for reviewing the result.
Geye: understand activity in context
The Geye product page explores people flow, queues, safety awareness, operational visibility, and perimeter monitoring. These camera-based use cases start with defined zones and observable activity. A queue signal, for example, can prompt a team to review conditions rather than assume the camera has the complete picture. Lighting, camera position, privacy, and missed detections all need consideration when evaluating a pilot.
Gnome: organize work with AI teammates
Gnome presents a local-first workspace concept where each AI teammate has a role, instructions, a working folder, and selected tools. Explore research, drafting, code review, and team handoffs as examples of work that can be divided into reviewable steps. Start with a small task, limit access to what it needs, and approve important actions before they run. A local-first approach does not remove the need to understand what a selected model or tool can access.
Explore first, validate before deployment
The product pages offer illustrative workflows and local previews, not live camera connections or running AI agents. Use them to choose a use case and identify the evidence, permissions, and review process your team needs. For Geye, that means testing signals against real conditions. For Gnome, it means checking outputs and access boundaries before entrusting a workflow to AI teammates.
