How can you claim 80–90% reduction if a chip runs workloads 40–60% of the time?

This is the right question. ConserveMode™ delivers savings at three distinct layers — not one single number. The 89% applies to idle-state intervals only. The 87% applies to inference requests via semantic caching. The ~51% is the whole-facility average. No chip achieves 80–90% across all conditions — but across all three layers combined, the total facility effect is approximately 51%. Each layer is independently auditable.

What does the 89% idle reduction mean exactly?

Between active workloads, an H100/H200 GPU typically idles at 600–700W. ConserveMode™ drops it to 75W using predictive scheduling — it knows when the next job is arriving and wakes the GPU just before it's needed. Zero latency impact, 89% less power during idle intervals. Validated on RunPod H200 instances across 31 global regions via nvidia-smi.

How does semantic caching produce 87% inference savings?

Many inference requests are semantically equivalent — slightly different wording, same underlying query. ConserveMode™ caches both exact and semantic matches. In V2.0 with mixed workloads: 51.4% are exact hits (0W), 15.2% are semantic hits (0W), 26% route to small 200W models, 5% to medium 350W, and only 2.3% need full 700W. Weighted average: 86W vs. 650W baseline = 87% reduction.

What is the total facility savings figure?

Approximately 51% at an 80% cache hit rate. IT equipment is 40–60% of total datacenter energy. Reducing IT load dramatically also reduces cooling — enterprise datacenters spend 30%+ on cooling vs. 7% at hyperscale. The combined effect across all infrastructure is approximately 51% whole-facility reduction.

Does this work for traditional (non-GPU) datacenters?

Yes. The predictive scheduling and caching principles apply to CPU-based servers as well. The absolute per-unit savings are lower (servers draw less than GPUs), but the percentage reductions are comparable. Enterprise datacenters running traditional workloads are actually among the highest-opportunity targets because they operate 30–50% less efficiently than hyperscale.

What are the upfront costs?

None. GTC uses a performance contract model — 20% of verified savings, paid only after savings are confirmed via IPMVP-compliant measurement. No hardware purchases, no upfront fees. You keep 80% from day one. For government facilities, this qualifies as an ESPC (Energy Savings Performance Contract) with no appropriated funds required.

Is this patented?

Yes. The technology is protected by PCT International Patent covering the broadcast distribution architecture, predictive workload scheduling, and semantic caching systems.

What is the DVBE certification?

Green Tech Coast Inc. holds California Disabled Veteran Business Enterprise (DVBE) certification. State and federal procurement regulations provide set-aside and preference advantages for DVBE contractors in energy services contracts. This positions ConserveMode™ favorably in competitive government procurements.

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