The HexaGrid Platform
Six interconnected pillars forming a complete AI infrastructure optimization control layer — unified through the QLLMe™ hybrid optimization engine.
Live wholesale electricity prices from five US ISO regions via the EIA API. The platform operates on real market data — not monthly averages. Grid volatility becomes a scheduling signal, not noise.
CAISO · ERCOT · NYISO · ISONE · PJMAn LSTM neural network generates 120-minute-ahead price forecasts in real time. That lead time is enough to defer any flexible workload away from price peaks and into price valleys automatically.
120-min Horizon · TensorFlow LSTMThe QLLMe™ engine combines classical optimization, QAOA quantum scheduling, and reinforcement learning in one unified pipeline. Multi-objective trade-offs — cost, carbon, capacity — resolved simultaneously.
QLLMe™ Engine · QAOA · QPU-ReadyA PPO reinforcement learning agent trained on 200,000 steps achieves 75% cost reduction versus flat-rate scheduling. It learns from live market behavior and compounds savings over time.
PPO Agent · 75% Cost ReductionLive carbon intensity from Electricity Maps across all five regions. The same workload can produce 3× more CO₂ depending purely on when and where it runs. HexaGrid makes that difference measurable and actionable.
Electricity Maps · Up to 50% CO₂ ReductionNVML telemetry monitors every GPU every 10 seconds — temperature, power, VRAM, ECC errors, and more. IsolationForest anomaly detection catches combined-metric failures before any single threshold trips an alert.
NVML · IsolationForest · 0–100 Health ScoreOne engine.
Three optimization layers.
QLLMe™ is what separates HexaGrid from conventional energy management tools. It doesn't apply a single algorithm — it runs three complementary optimization approaches in parallel, selecting the best decision for each workload in real time. As quantum hardware matures, the QAOA layer migrates to real QPU backends with zero code changes.