As India accelerates its transition to electric mobility, the two-wheeler segment remains at the forefront, particularly for middle-income and gig economy users. At the heart of this transformation is E3 Electric.AI — a startup that blends intelligent engineering, machine learning, and affordability into a next-generation EV solution. With a deep understanding of the Indian mobility ecosystem, the company is tackling persistent barriers such as battery safety, financing, and charging accessibility with a unique AI-powered approach.
P Sanjeev, Co-founder of E3 Electric.AI, brings over 25 years of experience spanning telecom, smartphones, and electric mobility. He, along with a team of 27 R&D engineers, founded the company with the vision of building EVs that go beyond just electrification — creating truly intelligent vehicles tailored for India’s real-world challenges. From fast-charging capabilities and smart diagnostics to patented features like Trip Assurance and geofencing based on real-time data, E3’s scooters are built to be safe, smart, and economical.
In a recent interview, Ritesh Kumar interacted with P Sanjeev, Co-founder, E3 Electric.AI, to discuss the startup’s innovations, market strategies, and vision to make EVs more accessible, intelligent, and financially viable for everyday Indian commuters.
Q: Could you tell us about your background and how E3 Electric.AI was founded?
Over the past two and a half decades, I’ve worked across the telecom, smartphone, and electric vehicle (EV) industries. I have extensive experience in the automotive space, and together with a team of 27 R&D engineers, we founded E3 Electric.AI. We realized that mobility in India needs more than just electrification — it requires intelligence to solve key issues like battery safety, charging infrastructure, financing, and resale.
Q: Why is the two-wheeler segment your primary focus, and not four-wheelers?
Two-wheelers are more affordable and relevant to India’s mobility landscape. The electric four-wheeler market is still expensive and slow-growing. Our mission is to solve for intelligent mobility, and in India, that’s primarily two-wheelers.
Q: What challenges do India’s middle-class and gig workers face with EVs?
First, they lack options in the affordable ₹80,000–₹1,00,000 range. ICE scooters offer 30+ choices; EVs barely have three good ones. Gig workers especially demand zero downtime, fast and ubiquitous charging, and reliability. We addressed these via fast-charging capability (Type 6 connector), portable batteries, and a unique AI-powered system called Trip Assurance, which we have patented. This monitors the battery’s condition, predicts issues, and ensures safety.
Q: What innovations are you bringing to improve charging and safety for gig workers?
Our removable battery system is portable like a suitcase, uses safe LFMP chemistry (LFP + manganese), and integrates safety features like thermal cutoffs. We support fast DC charging and “mobile-as-a-cluster” navigation through smartphones. AI-driven diagnostics inform financiers and resellers of battery life and condition, making EVs more financeable and resale-friendly.
Q: How are you leveraging AI in your scooters?
We use machine learning models to:
- Predict failures
- Estimate resale value
- Ensure battery and charging safety
- Customize ride settings (e.g., Smart Walk, Safe Slope Mode)
We’ve patented our safety and AI integration systems. Our scooters push 150+ CAN signals to the cloud for real-time analysis.
Q: How is E3 achieving a 40% lower Total Cost of Ownership (TCO) than ICE scooters?
Our scooters consume only ₹0.15/km compared to ₹2/km for ICE. We avoid costly hardware like NPUs and touchscreen clusters by utilizing the user’s smartphone. With fewer moving parts (no belt or transmission), maintenance costs are significantly reduced. Over three years, users save over 40%.
Q: How will you make your scooters financially accessible to gig workers and low-income users?
All vehicle data is shared via APIs with financiers and resellers. This enables better financing terms (EMIs around ₹1,500–₹2,000/month) and accurate resale pricing. Financiers also gain tools to track and immobilize vehicles, reducing risk.
Q: What role will AI play in the future of EV mobility in India?
AI is critical in predicting failures, enabling smart financing, integrating public charging, and enhancing rider safety. Much like how smartphones enabled new ecosystems (e-commerce, UPI), smart EVs will unlock insurance, servicing, AMC, and charging ecosystems.
Q: Can you explain your smart geofencing technology?
Traditional geofencing uses circular zones. We use isochrone-based zones — real, usage-based geofences. This improves accuracy and avoids unintentional immobilization of vehicles. It’s highly relevant for theft prevention and route tracking.
Q: Tell us more about your battery system and safety mechanisms.
Our battery is portable, charges via a simple 5A socket, and doubles as a power bank. We use non-cobalt LFMP chemistry for safety, and our smart BMS (Battery Management System) has thermal sensors and ML algorithms to detect anomalies. Safety is non-negotiable for us.
Q: What’s your strategy to capture 10% of India’s EV scooter market by 2028?
We aim to win customer trust with value-driven, intelligent products. Word of mouth from our first 1,000 users will be key. We plan a hybrid sales model (60% physical, 40% digital) with strong dealer networks. Our designs cater to both aspirations and practicality, especially for “Middle India.”
Q: What challenges do EV companies face in India?
Key issues include:
- Poor service preparedness
- Failure of critical components (battery, controller, motor)
- Overpricing due to unnecessary features (10-inch displays, ultra-fast acceleration)
- Lack of predictive maintenance systems
Many startups suffer due to unsustainable unit economics and unrealistic pricing strategies.
Q: How did you achieve a ₹100 crore pre-money valuation?
Our investors backed us based on our team’s experience, our 13 filed patents, and our first-principles approach. We raised approx. ₹16–17 crore in a rolling close to support product development and market entry.