T5 — Operate: Fleet Intelligence (Roadmap)
WARNING
Roadmap direction, not shipped. The fleet-intelligence domain is currently specified, with implementation planned. Everything below describes intended capability, not working code. Treat this tier as a roadmap placeholder, not an available feature.
T5 is the fleet-intelligence cognition layer that sits above the implemented fleet-delivery control plane (T4): drift detection, automated retraining triggers, and aggregate telemetry analytics across a fleet of deployed robots. "Fleet" means a fleet of robots, not Kubernetes clusters.
WARNING
Human-in-the-loop is the default; closed-loop retraining is a foot-gun. Fully autonomous retraining on production data can bake current degraded behavior into the next dataset, and drift detection needs statistical power that only exists at fleet scale. Fleet intelligence should default to the human-supervised stages (T5.0–T5.1), not the autonomous closed loop (T5.3). See the autonomy ladder.
🧱 Minimum Infrastructure
| Concern | What it would require (roadmap) |
|---|---|
| Edge infra | T4 infrastructure plus Azure IoT Operations for MQTT telemetry aggregation. |
| Cloud infra | T4 cloud plus Microsoft Fabric Real-Time Intelligence and drift / retraining services. |
| Autonomy | A separate axis (T5.0–T5.3): how much of the retraining decision a human delegates. |
🚀 Where to Go
This is a roadmap stub. For the intended architecture and the autonomy ladder, see the existing domain doc rather than a duplicate here:
- Fleet Intelligence: intended telemetry, dashboards, drift detection, and retraining triggers (roadmap / placeholder).
- Autonomy ladder (T5.0–T5.3): the ordered decision-authority stages, orthogonal to the T0–T4 infrastructure axis.