Aravolta

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Per-asset GPU fleet telemetry read directly from accelerator hardware while it runs: utilization, die/power temperature, power draw, and inferred workload pattern (training vs. inference) at serial-number granularity, carried continuously from deployment to retirement and joined to each device's maintenance record and a fitted per-asset depreciation/life-expectancy curve. This is hardware-condition ground truth on AI-accelerator collateral — a class of data that exists nowhere else, because hyperscalers publish utilization only as aggregate commentary and OEMs see only RMA rates.