The Digital DNA™ platform
Three connected layers of intelligence — from understanding battery materials at the smallest scale, to linking every piece of data, to AI that predicts what happens next.
Three intelligence layers
Click each layer to see how it works.
A reference library that profiles every important battery material — cathodes, anodes, electrolytes and separators. It is built from 12+ years of lab research, and it is the foundation every prediction stands on.
- Material fingerprinting — each material gets a unique, searchable signature.
- Cross-chemistry comparison — every major chemistry measured the same way, side by side.
- Failure-mode library — known ways batteries fail, mapped back to material traits.
- Continuously growing dataset — the library expands with every new material studied.
Technical detail
Materials are characterised using XRD (crystal structure), XPS (surface chemistry), EIS (electrochemical behaviour) and electron microscopy. Profiles span NMC, LFP and NCA cathode families alongside next-generation chemistries.
One connected, searchable record that links every stage of a battery's life — mine, material, electrode, cell, pack and field behaviour — so nothing is lost and everything stays traceable.
- End-to-end data lineage — every data point links forward and backward with no gaps.
- Tamper-proof checkpoints — verified records at every critical handoff.
- Real-time ingestion — factory, vehicle and grid data flows in continuously.
- Full provenance — the complete origin and history of every material is preserved.
Technical detail
Streaming pipelines ingest from MES, BMS and SCADA systems, with blockchain-anchored checkpoints for tamper-proof verification and sub-second trace latency across all six supply-chain layers.
AI that forecasts how a battery will age, warns of fire risk weeks ahead of time, and tunes day-to-day usage to make batteries last longer.
- Ageing forecasts — clear predictions of how capacity will fade over time.
- Early fire warning — safety risks flagged well before they become dangerous.
- Smarter battery management — usage recommendations that protect lifetime.
- Quantified confidence — every prediction comes with a measure of how certain it is.
Technical detail
Built on physics-informed machine learning (PINN): electrochemical models are fused with ML so predictions respect real battery physics and carry quantified uncertainty.
A living mirror of every battery
Every battery pack gets a digital twin — a continuously updated model that reflects its make-up, its history and its real-time state. It lets operators fix problems before they happen and make accurate warranty decisions with confidence.
- Always current — the twin updates as live data arrives from the field.
- Proactive maintenance — issues are caught early, before they cause downtime.
- Confident warranties — decisions backed by each pack's true health.
See Digital DNA™ in action
Walk through the platform with our team — see how the three layers connect material science, live data and AI for your batteries.