Use case blueprint
Search zones and events while keeping high-risk outcomes human-reviewed.
Security video can affect people and physical spaces, so product claims must be precise. Ayneye is positioned as evidence and review infrastructure, not an autonomous enforcement system. It can surface events, zones, time spans, confidence, and review notes while keeping identity, intent, discipline, emergency, and access-control decisions outside automated scope.
| Stage | Implementation detail |
|---|---|
| Map zones | Define safe zones, camera names, and review boundaries before processing. |
| Process representative footage | Run a bounded pass on footage that includes normal and edge-case scenes. |
| Review evidence | Open the evidence bundle and compare each detected event with the footage. |
| Classify risk | Separate low-risk search from high-risk escalation that requires human approval. |
| Document policy | Record which actions remain read-only and which require a human policy gate. |
Open artifacts before increasing limits. A strong evaluation compares artifact state with the original footage and records misses, ambiguity, confidence, and cost.
The goal is not a generic demo; the goal is deciding whether this workflow should become a paid pilot, remain a small beta test, or require escalation.