HexaGrid™ — Platform
Platform

Six pillars.
One control plane.

HexaGrid unifies grid intelligence, price forecasting, quantum-hybrid scheduling, RL dispatch, carbon routing, and GPU telemetry into a single operational layer — driven by the QLLMe™ engine.

Six Pillars

Each layer is independently functional. Together they form a closed-loop system: real-time data feeds the forecaster, the forecaster feeds the scheduler, the scheduler feeds the RL agent, and telemetry feeds back into every decision.

01 / 06
Grid Intelligence

Live wholesale electricity prices from all five US ISO regions via the EIA API — cached with a 15-minute TTL and updated continuously. Grid volatility stops being noise and becomes a precise scheduling input.

CAISO · ERCOT · NYISO · ISONE · PJM
02 / 06
📈
Predictive Forecasting

A TensorFlow LSTM trained on two years of historical price data generates a 120-minute forward forecast in real time. That window is enough lead time to defer any flexible workload away from a price spike before it arrives.

LSTM · 1.92% MAPE · 120-min Horizon
03 / 06
Hybrid Optimization Core

The QLLMe™ engine runs three approaches in parallel: classical COBYLA/BFGS for low-latency deterministic decisions, QAOA variational quantum circuits for combinatorial scheduling, and PPO reinforcement learning for adaptive dispatch. The best decision wins.

QLLMe™ · QAOA · Cirq · QPU-Ready
04 / 06
🤖
Adaptive Dispatch

A Stable Baselines 3 PPO agent trained over 200,000 steps learns from live market behavior — not simulated price curves. Benchmarked at 15–30% cost reduction versus flat-rate scheduling in live grid conditions. Savings compound as the agent adapts.

PPO · SB3 · 200k Steps · 15–30% Reduction
05 / 06
🌱
Carbon Intelligence

Live carbon intensity from Electricity Maps across all five ISO regions. The same GPU workload can produce 3× more CO₂ depending entirely on when and where it runs. HexaGrid makes that difference visible and automatically routes against it.

Electricity Maps · Scope 2 · Up to 50% CO₂
06 / 06
🖥️
Hardware Feedback Loop

NVML telemetry polls every GPU every 10 seconds — temperature, power draw, VRAM utilisation, ECC error counts, fan speed. An IsolationForest anomaly detector catches combined-metric failure signatures before any single threshold would fire an alert.

NVML · IsolationForest · 0–100 Health Score
15–30%
Cost reduction
RL dispatch vs flat-rate
50%
Carbon reduction
carbon-first routing
120m
Price forecast horizon
LSTM model
5
Live ISO regions
simultaneous feeds
QLLMe™ Engine

Three optimization layers.
One unified decision.

QLLMe™ is what separates HexaGrid from conventional energy management tools. Rather than committing to a single algorithm, it runs three complementary approaches in parallel and selects the optimal decision per workload in real time.

Cost, carbon, capacity, and PUE are resolved simultaneously as a multi-objective problem — not sequentially as competing constraints. No manual trade-off tuning required.

As quantum hardware matures, the QAOA layer migrates to real QPU backends via IBM Quantum or IonQ — with zero code changes to the rest of the platform.

📐
Classical Optimization
COBYLA / BFGS solvers — deterministic, sub-millisecond latency for time-critical dispatch decisions
QAOA Quantum Scheduler
Variational quantum circuits for combinatorial job-to-resource assignment — up to 15-qubit problems, QPU-ready via Cirq
🧠
PPO Reinforcement Learning
Adaptive dispatch agent trained on 200k steps — learns from live market conditions and compounds savings over time
⚖️
Multi-Objective Scoring
Cost · carbon · capacity · PUE — weighted per operator priority, resolved simultaneously not sequentially
🔁
Hardware Feedback Integration
GPU telemetry and anomaly signals feed back into every scheduling cycle — protecting compute while optimizing it

Deploys in 15 minutes.

HexaGrid runs on any NVIDIA GPU infrastructure — no new hardware required, no vendor lock-in. A single uvicorn process, a static dashboard, two API keys.

Bare Metal
WSL2
AWS EC2
Docker
Azure
Any NVIDIA GPU