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  • 10+
    Years of research
  • 900x
    Faster diagnostics
  • 10x
    Efficiency
  • 85-100%
    Less CO2 emissions
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Optimize BESS performance & lifetime

Accurate, AI-driven battery diagnostics

that reduce operational risk, improve availability, and extend asset lifetime

seamlessly integrated into BESS operations.

 

BESS Performance & Risk Management

Protect performance and reduce risk from commissioning onward

Large-scale BESS assets carry significant financial and technical risk if battery quality issues are discovered only after installation. CeLLife’s Electrical Fingerprint (EFP™) technology enables ultra-fast, module- and rack-level incoming quality control to verify battery condition before commissioning and throughout operation.

By screening every module in seconds, CeLLife helps prevent weak or deviating batteries from entering the system. This establishes a traceable baseline from day one, reduces commissioning and warranty uncertainty, and protects long-term system performance and profits.

Enable predictive maintenance and maximize BESS availability

CeLLife supports condition-based and predictive maintenance through fast, non-disruptive diagnostics at module and rack level. Instead of waiting for failures, early warning signs are detected while the system is operating normally.

This allows targeted preventive actions before issues escalate, reduces unplanned downtime, and avoids unnecessary maintenance work. CeLLife delivers clear actionable diagnostics and recommendations without requiring internal data teams or complex analytics from the operator.

 

Predictive maintenance for BESS
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Unlock lifecycle value and regulatory readiness

CeLLife provides fully traceable battery intelligence across the full BESS lifecycle, from commissioning to end-of-life, creating clear documentation for warranty, compliance, and Battery Passport requirements. When issues arise, the system’s history is already documented and explainable.

With this foundation, operators can make informed end-of-life decisions on reuse, refurbishment, or recycling. This improves asset confidence, reduces lifecycle risk, and supports long-term sustainability.


OUR CLIENT TESTIMONIALS

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“CeLLife technology is integrated into our O&M delivery, using AI-driven electrical fingerprint to provide deeper asset health insights and support improved availability and ROI significantly.”

 

Sean Stephenson - Group CEO of LBS Group

 

Sean Stephenson - Group CEO, LBS Group

 

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Applications

Battery, perfected. CeLLife.
Battery, perfected. CeLLife. Battery, perfected. CeLLife.
Detect mechanical defects
Detect electrochemical defects
Condition forecast
Root cause analysis
Cell disparity
Charge and discharge performance

CeLLife's EFP™ for BESS

Gain insight quickly

1. Adapt diagnostics to your BESS configuration

CeLLife’s EFP™ technology is configured to match your BESS architecture, battery chemistry, and system layout. The same core measurement method is applied consistently, while analysis parameters are tuned to your specific use case — from commissioning checks to long-term operation.

Focus: Flexibility across BESS designs without changing hardware or processes.

2. Capture high-resolution health data in seconds

Each measurement captures a dense electrical fingerprint at module or rack level in seconds. This creates a reliable, high-resolution dataset without extended testing, cycling, or system interruption.All data is automatically stored and structured, enabling consistent comparison across assets, sites, and time.

Focus: Fast, repeatable data capture at BESS scale.

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3. Translate data into actionable lifecycle insight

CeLLife’s analytics layer transforms measurement data into clear indicators for condition, performance, and remaining lifetime. Trends, deviations, and inefficiencies become visible early, supporting informed decisions across operation, optimisation, and end-of-life planning.

Focus: Turning diagnostics into practical lifecycle decisions.



GAIN GREATER PROFITS BY OPTIMIZING THE PRODUCTION AND UTILIZATION OF EVERY BATTERY

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