From preventing catastrophic thermal events to optimizing dispatch revenue—explore how our AI-powered intelligence layer transforms BESS operations across critical use cases.
Thermal runaway is the most critical safety risk in lithium-ion battery systems. Once initiated, it can cascade through an entire BESS installation within minutes, causing catastrophic damage and safety incidents. Zaptiv provides the early warning intelligence that gives operators the time to intervene before thermal cascade begins.
Real-time temperature gradient analysis across cell strings with sub-minute granularity
Early-stage anomaly detection using voltage, impedance, and temperature correlation patterns
Automated pre-trip alerts with BMS isolation recommendations before threshold breach
Industry Impact
4+ weeks average advance warning time
Before thermal runaway threshold is reached
Cell Temperature Map (°C)
Cell C7 - Thermal Anomaly Detected
Temperature rising 2.3°C/min. Recommend BMS isolation. Time to threshold: 12 min.
Fleet Overview
BESS-TN-2024-0847
Replacement Predicted
Q3 2029
Confidence
95.4%
RUL
1,247 Days
Battery degradation is inevitable—but unexpected degradation isn't. Zaptiv's machine learning models continuously analyze charge cycles, depth of discharge patterns, temperature exposure, and impedance trends to predict remaining useful life (RUL) with industry-leading accuracy. Know exactly when and where capacity fade will impact your operations.
Capacity fade modeling using electrochemical degradation signatures from operational data
Fleet-level health scoring with cell-level granularity for targeted maintenance
Replacement planning with procurement lead-time integration
Customer Impact
25% extended battery lifecycle
Through optimized operating envelope management
Grid-scale BESS assets are revenue-generating machines—but aggressive dispatch can accelerate degradation while conservative dispatch leaves money on the table. Zaptiv's SoC optimization engine balances revenue maximization with long-term asset preservation, ensuring you're always operating at the optimal point.
Dynamic SoC window optimization based on real-time degradation models
Grid services revenue tracking for ancillary services, frequency regulation, and peak shaving
Weather and price forecasting integration for predictive dispatch planning
Customer Impact
15-20% revenue improvement
Through optimized dispatch scheduling
Dispatch Analytics
Real-time optimization
Today's Revenue
₹4.2L
↑ 18% vs baseline
SoC Efficiency
94.7%
↑ 3.2% vs last week
Dispatch optimized for current SoH conditions
EMS Integration Diagnostics
Connected to Schneider SCADA
BMS
Active
PCS
Active
HVAC
Active
Setpoint command to PCS showing 450ms average delay (threshold: 200ms)
Data Points/sec
2,847
Latency
12ms
Energy Management Systems (EMS) are critical for BESS operations—but when they lag, glitch, or misreport, operators lose visibility and control. Zaptiv provides an independent diagnostic layer that monitors your EMS performance, detects communication anomalies, and identifies integration issues before they impact grid operations.
EMS lag detection with sub-millisecond precision and automatic alerting
Setpoint deviation analysis to identify control loop issues and tuning problems
Native integration with Schneider, Siemens, ABB, and other major EMS/SCADA platforms
Operational Impact
99.7% data integrity
Across all integrated data points
Every BESS deployment has unique challenges. Schedule a technical consultation to understand how our predictive analytics platform can address your specific operational requirements.
Thermal Safety
SoH Prediction
Dispatch Opt.
EMS Diagnostics
Engineering-first conversations. No sales pressure.