EcoDispatch AI Production Engine

NextStep Hacks 2026 • Earth Forward • YC Candidate Sprint

GitHub MIT
🌱 Earth Forward • Sustainable AI Compute Dispatcher

Compute When Clean Energy Surges.

Autonomous marginal carbon intensity forecasting and polynomial-time deadline scheduling. Slashing AI cluster carbon emissions by up to 68% with verifiable SHA-256 ESG certificates.

Select Power Grid:
US-CAISO (California): Midday Duck-Curve Solar Valley
Marginal Carbon Rate Live
84.2 gCO₂eq/kWh
Unmanaged Peak: 460.0 g/kWh
Renewable Power Mix Solar+Wind
76.4% clean generation
Clean Generation: 17,300 MW
Next Green Valley Low Carbon
+2h → +9h
Peak Clean Hours: 7 Hours Low-CO₂
Avoided Emissions Verified
21.51 kg CO₂ (-55.0%)
Total Workloads: 5 Active Jobs

24-Hour Marginal Carbon Curve & Green Valley Windows Dynamic Forecast

Marginal emissions over next 24 hours. Shaded emerald regions denote zero-curtailment clean windows.

Green Valley (<100g)
Standard Grid
Fossil Peaker (>350g)

Autonomous Workload Studio

Select presets or inject custom delay-tolerant AI workloads into the constraint optimizer.

+ Inject Custom Workload Live SLA Optimizer

Autonomous Schedule & Avoided Carbon Analysis

Dispatched into optimal renewable windows with 0% SLA violations.

Workload & Cluster Energy Green Window Baseline CO₂ Optimized CO₂ Avoided CO₂ Clean %
Optimizer: Polynomial Dynamic Time-Indexed Bin Packing Zero SLA Violations
TAMPER-PROOF ESG CERTIFICATE SEC & EU CSRD Compliant
ECO-US-CAISO-20260920-8F92A1
SHA-256 Digest: 575ffef6c86d8dfd6eef1355c23b7af844be4d1cf610a126fdae0733b5e62013
Net Avoided CO₂
21.51 kg CO₂
Carbon Reduction
-55.0%