Use case blueprint
Embed video intelligence into SaaS products with REST, artifacts, dashboard onboarding, and agent-safe APIs.
A developer platform needs predictable API behavior, tenant isolation, visible limits, stable artifact contracts, and a way to show evidence in the UI. The integration should start with REST and dashboard artifacts before any advanced MCP tool invocation or production-scale billing path.
| Stage | Implementation detail |
|---|---|
| Tenant mapping | Map your customer/account/workspace model to an Ayneye beta tenant. |
| Source registration | Create video records through REST or the dashboard with clear source metadata. |
| Artifact retrieval | Fetch scene_graph.json, evidence_bundle.json, timeline.json, and cost.json by video ID. |
| Evidence UI | Show users the supporting time spans and review notes behind each answer. |
| Product gate | Expose higher limits only after cost, quality, errors, and review boundaries are understood. |
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.