Our CEO named to Forbes Korea 30 Under 30
March 2026
BATTERY LIFECYCLE INTELLIGENCE
A battery management platform built on a physics-informed AI life prediction model.One continuous data record from deployment (BOL) through operation (MOL) to end of life (EOL).





When service ends, each battery has to be cleared for reuse or sent to recycling.That call is only as good as the operating record behind it.Most sites either don't keep that record or lose it between stages.
Issue 01
Operating data disappears when a battery leaves the site.Its history never reaches the people making the call.
Issue 02
Years of degradation and remaining life are inferred from a single final measurement.
Issue 03
Without evidence, decisions default to the safe side.Batteries that could be reused get shredded instead.
Our approach: capture data where batteries operate, and carry the same record all the way to the final decision.
Designed around reused batteries.Handles mixed makers and specs, incomplete histories, and uneven aging.Works just as well for new batteries.
BOLDeployment
Go/no-go based on predicted remaining life · Expected service life and economics
MOLOperation
Continuous operating logs · Early anomaly alerts · State-aware charge and discharge control
An ensemble of electrochemical modeling and deep learning.Physics rules out impossible answers. Deep learning picks up subtle degradation patterns.Reliable even when a battery's history is incomplete.
01 · Sense
Cell-level voltage, current, temperature, and SOC time series.Operating history included.
02 · Reason
Electrochemical model and Kalman filter alongside CNN, LSTM, and attention, combined in a physics-informed ensemble.
03 · Learn
Retrained on live data from JDMS and JD EMS.Accuracy improves with every new deployment.
| SOH prediction error · Lower is better | MAE | |
|---|---|---|
| Joodra | 0.62pp | |
| Conventional | 3.24pp | |
1/5
the prediction error of conventional methods.
Internal benchmark · n=1,428
Start with any stage.Data from each stage carries into the next.
Battery diagnostics · Deployment and end-of-life decisions
Battery monitoring · Early anomaly warnings
ESS grid control · Second-life battery operations
R2 recycling SCM · Plant operations and audit readiness
Built-in BMS diagnostics · ESS EMS · ITAD software
JD Plan · JDMS · JD EMS · JD Works
JDMS · KR
62+
8 months in commercial operation14,009 anomalies caught early. Zero incidents.Now expanding to defense drone batteries.
JD Works · US
3
200+ active users · About 30% less admin work (customer-measured)
JD Plan · JD EMS
2
Co-developing ESS built on reused batteries.Jointly validating the AI life prediction model.
| MoU | LG Energy Solution | Co-developing grid ESS with reused batteries |
|---|---|---|
| PoC | LS ELECTRIC | Joint validation of the AI battery life model |
| Customer | KORAIL | Station UPS battery monitoring · JDMS |
| Customer | Paladin Envirotech and others | R2-certified U.S. recycling plants · JD Works |