Modules and AI Agents

🔧 O&M Optimization

Optimize maintenance schedules, reduce costs, and maximize uptime with AI-powered predictive maintenance.

🛡️ Insurance & Risk Management

Transform your insurance operations with AI-driven risk management, live monitoring, and instant parametric payouts.

📈 Energy Trading

Predict the best buy/sell price arbitrage to make high-certainty trades in intraday energy markets.

🌬️ Turbine-Specific Wind-Flow Graph Net

Modeling the unique wind conditions and performance of each turbine, taking into account its exact location, local terrain, and real-time operational data.

Result: Improved accuracy on production forecasting

🗓️ Maintenance-Market Window

AI agent balances expected market price, forced-outage probability, and crew calendar to optimize START-MAINTENANCE versus DEFER decisions in hourly increments. Automates "negative-price tomorrow, fix today" logic.

Outcome: Direct EBITDA uplift within existing maintenance budgets

🤖 AI Crew-Quality Oracle

3B-parameter on-device chatbot interviews technicians via mobile app, extracting root-cause analysis, parts used, and labor minutes. Human responses are labelled and tagged and integrated into existing device failure probability models.

Outcome: Enhanced predictive maintenance accuracy, reduced repeat failures

🔋 Battery-Buffered Bid-Sizer

Model to calculate minimum MWh storage required for 98% firmness target on 2-hour evening-peak bids.

Outcome: Trims battery CAPEX by 10–15%

Outcome: Maintains near-zero trading penalties

Outcome: Directly improves project IRR

📝 Regulatory Reporting Co-Pilot

Auto-fill official SAWEM XML templates from existing O&M database, attaches data-quality attestation, and flags impending non-compliance.

Outcome: Monthly compliance drops from 3 days to 30 minutes

Outcome: Eliminates disqualification risk from future tenders

📈 Penalty-Insurance Meta-Forecast

Model analyzes 24-hour forecast versus actuals to generate 5th–95th percentile error bands per half-hour slot. Live dashboard displays "Penalty-at-Risk", enabling traders to hedge or defer maintenance before 18:00 gate closure.

Impact: Up to 70% reduction in unplanned trading penalties

☁️ Cloud-Shadow Nowcast for Solar

IP sky-cameras feed conv-LSTM predicting shadow motion 0–30 minutes ahead per string. Outputs probabilistic ramp-rate distributions to pre-position battery SOC setpoints.

Impact: Eliminates unnecessary cycling costs, avoids 30-second ramp violations triggering ancillary-service penalties