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M-01 · Workload

AI Workload Scheduler

Real-time agentic decisions on task execution, resource allocation, and escalation — running autonomously at 1000 km altitude.

Live simulation · 1000 km LEO · 105 min orbit · 25 TFLOPS / node
Maargin · Autonomous Satellite Workload Scheduler

Agentic AI scheduler running aboard a LEO satellite node — making real-time decisions on task execution, resource allocation, and escalation using a fine-tuned on-device SLM. Each decision weighs battery state, orbital phase, CPU headroom, and ISL topology to determine whether to run locally, queue, or escalate to cluster head.

Telemetry · 30 min window
CPU —
Memory —
Battery —
Temp —
CPU —
Memory —
Battery —
Temp —
Power —
Phase —
⚠ Visual demonstration only — this dashboard does not display data from an actual satellite or live system. All telemetry, orbital states, and AI decisions shown are simulated. ⚠ Visual demonstration only — this dashboard does not display data from an actual satellite or live system. All telemetry, orbital states, and AI decisions shown are simulated. ⚠ Visual demonstration only — this dashboard does not display data from an actual satellite or live system. All telemetry, orbital states, and AI decisions shown are simulated.