Consumer Electronics

Your Users Want All-Day Battery. For Years.

Physics-informed battery intelligence that fits in 110KB and delivers 2x longer lifespan

What Users Experience Today

  • 18-month battery degradation
  • Daily charging anxiety
  • Slow “fast” charging
  • 43% return rate for batteries

What BattGenie Enables

  • 3+ years at 80% capacity
  • All-day battery after 1000 cycles
  • 5 minutes to 50% safely
  • <5% warranty claims

110KB of Physics That Changes Everything

Our models understand what's happening inside the battery - SEI growth, lithium plating, thermal stress - not just voltage. This means:

98.7% SOC accuracy

Users know exactly how much battery they have

2x lifespan

1000+ cycles to 80% capacity

Safe fast charging

Prevent degradation while charging quickly

No hardware changes

Software upgrade to existing designs

"BattGenie reduced our warranty claims by 43% and increased battery satisfaction from 3.2 to 4.7 stars. The 110KB footprint meant zero hardware changes."

- A major consumer electronics partner

Development

BattStudio

Test strategies virtually

 Production

BMS Solutions

Embed intelligence

Analytics

BattOps

Monitor field performance

10M+

Protecting Devices

98.7%

SOC Accuracy

Zero

Thermal Incidents

8

Week Integration

Electric Vehicles

Unlock 20% More Range From The Same Battery

98.7% SOC accuracy and physics-informed intelligence for OEMs, Tier 1s, and fleet operators

Current Reality

  • ±10% SOC uncertainty
  • 20% capacity held in reserve
  • 400-mile practical range
  • $100B in stranded capacity
  • 0% battery oversizing

With BattGenie Physics

  • ±1.3% SOC precision (98.7%)
  • Only 5% safety margin needed
  • 480-mile usable range
  • Full utilization of every kWh
  • Right-sized packs save $3,000/vehicle

Major OEM

Achieved 520-mile range with 15% smaller battery - saved $2,400 per vehicle

Fleet Operator (1,000 EVs)

92% reduction in roadside failures, 15% more usable range per vehicle

The Physics Advantage

We model SEI growth, lithium plating, and thermal propagation - not just voltage curves. This means accurate predictions even for new chemistries and extreme conditions.

For OEMs & Tier 1s

BattStudio

Optimize pack design with digital twins. Reduce development time by 6 months.

For Production

BMS Solutions

98.7% SOC accuracy in 110KB. Works with existing hardware.

For Fleet Operations

BattOps

Predict failures 90 days ahead. Optimize 1 to 100,000 vehicles.

10M+

Protecting Devices

98.7%

SOC Accuracy

Zero

Thermal Incidents

8

Week Integration

BESS

Unlock 20% Hidden Capacity. Add $2M Revenue Per 100MWh

98.7% SOC accuracy and 90-day failure prediction transform unpredictable assets into reliable revenue

Traditional BESS Operation

  • ±10% SOC uncertainty
  • 20-80% operating window
  • 60MWh usable (100MWh system)
  • $4.4M annual revenue
  • 7-year payback

Physics-Informed BESS

  • ±1.3% SOC accuracy (98.7%)
  • 5-95% operating window
  • 90MWh usable capacity
  • $6.6M annual revenue
  • 4.5-year payback

110KB of Physics That Changes Everything

Our models understand what's happening inside the battery - SEI growth, lithium plating, thermal stress - not just voltage. This means:

98.7% SOC accuracy

Users know exactly how much battery they have

2x lifespan

1000+ cycles to 80% capacity

Safe fast charging

Prevent degradation while charging quickly

No hardware changes

10M+

Protecting Devices

98.7%

SOC Accuracy

Zero

Thermal Incidents

8

Week Integration

Venkat Subramanian

CTO, Chief Scientific Advisor, and Co-Founder

Prof. Venkat Subramanian is currently the Ernest Dashiell Cockrell II Professor of Mechanical & Material Science Engineering at the University of Texas, Austin.

His research interests include energy systems engineering, electrochemical engineering, computationally efficient algorithms for state-of-charge (SOC) and state-of-health (SOH) estimation of lithium-ion batteries, multiscale simulation, and design of energetic materials, kinetic Monte Carlo methods, model-based battery management system for electric transportation, and renewable microgrids and nonlinear model predictive control. Prof. Subramanian was awarded the Dean’s award for excellence in graduate study in 2001 for his doctoral research.

He is a Fellow of the Electrochemical Society and a past Technical Editor of the Journal of the Electrochemical Society. He was also the chair of the IEEE Division of the Electrochemical Society. His codes for Lithium-ion batteries are the fastest reported in the literature and his algorithm for solving index 1 nonlinear DAEs is the most robust compared to any other algorithm reported as of today.

Prof. Subramanian received his B.Tech. degree in Chemical and Electrochemical Engineering from the Central Electrochemical Research Institute (CECRI), Karaikudi, India, in 1997 and the Ph.D. degree in Chemical Engineering from the University of South Carolina, Columbia, SC, USA, in 2001.

Manan Pathak

CEO and Co-Founder

Dr. Manan Pathak is the Chief Executive Officer and co-founder of BattGenie.

He earned his PhD at the University of Washington, where he obtained his graduate thesis on model-based Battery Management Systems. He has 7+ peer-reviewed publications with over 300 citations, and extensive experience with physics-based battery models, numerical methods and derivation of optimal charging profiles.

Chintan Pathak

CPO and Co-Founder

Dr. Chintan Pathak is the Chief Product Officer and co-founder of BattGenie.

He earned his PhD from the University of Washington and he obtained his graduate thesis on optimal locations of battery charging stations in the state of Washington. He has over 13 years of experience in software engineering and embedded systems.

Akshay Subramaniam

Battery Modeling Scientist

Akshay Subramaniam leads electrochemical model development and identification tasks at BattGenie. He also contributes towards BMS algorithm development and validation, and helps maintain our models, databases, and testing pipelines. He received his Ph.D. from the University of Washington during which he gained extensive experience in the development of control-oriented electrochemical models. He has 10+ peer-reviewed publications and is proficient in several aspects of battery systems engineering including numerical simulation techniques, optimization for design and fast charging, parameter estimation, and battery data analysis.

Taejin Jang

Battery Simulation Scientist

Dr. Taejin Jang is a Battery Simulation Scientist at BattGenie. Dr. Jang received his Ph.D in Materials Science from University of Texas at Austin and an MS in Chemical Engineering from UW. He also has BS and MS degrees in Materials Science & Chemical Engineering from Yokohama National University in Japan. He spent three years in the automotive devices industry at Samsung Electronics. He has 7+ years’ experience in battery modeling and simulation, encompassing Li-ion and next-generation batteries.

Bing Syuan Wang

Senior Battery Software and Data Engineer

Bing Syuan Wang is the Senior Battery Software and Data Engineer at BattGenie.
He earned his Masters in Electrical Engineering from the University of Washington. He has over 6 years’ experience in software engineering and in working with battery data.

Aditya Parsai

Fullstack Software Engineer

Aditya Parsai is a Fullstack Software Engineer at BattGenie. He graduated in Civil Engineering from IIT(BHU). With 8 years’ experience, he contributes to helping businesses succeed in the digital space by staying attuned to the evolving tech landscape. His work spans from front-end development to back-end system engineering, ensuring smooth integration and functionality. He recognizes the importance of storytelling and is adept in translating complex ideas into user-friendly interfaces to enhance user experiences.