Leishen Power \China

Leishen Power was a Chinese battery technology company founded in 2016 that aimed to develop and manufacture advanced lithium-ion batteries for electric vehicles and energy storage systems. The company positioned itself during China's aggressive push toward EV adoption and renewable energy infrastructure, attempting to compete in a market dominated by CATL, BYD, and international players like LG Chem and Panasonic. With $250M in funding, Leishen sought to achieve breakthrough energy density and cost advantages through proprietary cell chemistry and manufacturing processes. The timing seemed perfect—China's NEV (New Energy Vehicle) mandate was accelerating, and battery demand was exploding. However, Leishen entered a capital-intensive, scale-dependent industry where established players had 5-10 year head starts in manufacturing optimization, supply chain integration, and customer relationships with major automakers. The company struggled to achieve the manufacturing yield rates and cost structures necessary to compete, while simultaneously burning through capital on R&D and production facility buildout. By 2024, despite significant investment, Leishen could not secure the tier-1 automotive contracts needed to justify continued operations in an increasingly consolidated market.

SECTOR Industrials
PRODUCT TYPE CleanTech
TOTAL CASH BURNED $250.0M
FOUNDING YEAR 2016
END YEAR 2024

Discover the reason behind the shutdown and the market before & today

Failure Analysis

Failure Analysis

Leishen Power died from the classic hardware startup trap: entering a capital-intensive, scale-dependent market against entrenched incumbents without sufficient differentiation or customer lockup. The...

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Market Analysis

Market Analysis

The global battery industry has evolved into a highly consolidated, scale-driven oligopoly since Leishen's founding in 2016. CATL (Contemporary Amperex Technology Co. Limited) emerged...

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Startup Learnings

Startup Learnings

Capital intensity is a moat for incumbents: In hardware businesses requiring $1B+ to reach minimum viable scale, early entrants build insurmountable advantages. If you're...

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Market Potential

Market Potential

The battery market remains enormous and growing despite Leishen's failure. Global battery demand is projected to reach 4,500 GWh by 2030 (up from ~700...

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Difficulty

Difficulty

Battery manufacturing represents one of the highest difficulty rebuilds in all of hardware. The barriers are extreme: (1) Materials science R&D requiring 3-5 year...

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Scalability

Scalability

Battery manufacturing has brutal unit economics that only improve at massive scale. This is a classic 'scale or die' business with high fixed costs...

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Rebuild & monetization strategy: Resurrect the company

Pivot Concept

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AI-powered battery health diagnostics and lifecycle optimization platform that extends EV battery life by 20-30% and enables predictive maintenance, targeting the $50B secondary battery market. Rather than manufacturing batteries, build the intelligence layer that maximizes value from existing batteries. The platform uses edge AI to analyze real-time battery telemetry (voltage, current, temperature, impedance across individual cells), predict degradation patterns, and optimize charging/discharging strategies. Revenue model combines SaaS subscriptions from fleet operators, licensing to OEMs for integration into BMS (Battery Management Systems), and transaction fees from battery warranty/insurance products. The wedge is commercial EV fleets (delivery vans, buses, trucks) where battery degradation directly impacts TCO and operators are desperate for solutions. As batteries degrade, range decreases and replacement costs ($15K-$40K) devastate fleet economics. Voltaic Forensics provides: (1) Predictive alerts 3-6 months before failure, enabling proactive replacement scheduling, (2) Optimized charging protocols that reduce degradation by 20-30% through AI-learned strategies, (3) Residual value certification for secondary markets (repurposing EV batteries for stationary storage), (4) Warranty/insurance underwriting data. The platform is hardware-agnostic, working with any battery chemistry and any vehicle OEM, creating network effects as more data improves prediction accuracy. This pivots from capital-intensive manufacturing to capital-efficient software, from commodity products to high-margin services, and from competing with CATL to partnering with the entire ecosystem. The TAM is massive: 40M EVs on road by 2025, each with $20K-$40K of battery value requiring optimization. Fleet operators would pay $50-200/vehicle/month for 20% battery life extension. OEMs would pay licensing fees to reduce warranty costs (battery warranties are 8-10 years, representing huge liabilities). The business scales with software economics (90%+ gross margins) while addressing the industry's biggest pain point: battery degradation and end-of-life management.

Suggested Technologies

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Edge AI inference (TensorFlow Lite, ONNX Runtime) for real-time battery telemetry analysis on vehicle hardwareTime-series forecasting models (LSTM, Transformer architectures) for degradation prediction trained on millions of charge cyclesPython/FastAPI backend for data ingestion, model serving, and fleet management APIsClickHouse or TimescaleDB for high-performance time-series data storage (billions of data points per fleet)React/Next.js dashboard for fleet operators with real-time battery health visualizationKubernetes for scalable model deployment and multi-tenant SaaS architectureCAN bus integration libraries for vehicle telemetry extraction (python-can, CANopen)AWS IoT Core or Azure IoT Hub for secure device connectivity and data streamingMLflow for model versioning, A/B testing of optimization strategies, and continuous learningStripe for subscription billing and usage-based pricingSalesforce or HubSpot for enterprise sales pipeline (targeting fleet operators and OEMs)Grafana for internal monitoring of model performance and data quality

Execution Plan

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Phase 1

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Wedge: Partner with 2-3 commercial EV fleet operators (delivery companies, transit agencies) with 50-200 vehicles each. Offer free pilot in exchange for data access and testimonials. Install lightweight data loggers (if OEM APIs insufficient) to capture battery telemetry. Build initial dataset of 1M+ charge cycles across diverse use cases (urban delivery, highway, cold weather). Develop baseline degradation models using open battery research datasets (NASA, Oxford) and validate against pilot data. Deliver simple dashboard showing battery health scores and predicted replacement timelines. Goal: Prove 15-20% improvement in degradation prediction accuracy vs. OEM estimates, secure 2 paid contracts at $100/vehicle/month.

Phase 2

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Validation: Expand to 10 fleet customers and 2,000+ vehicles. Implement closed-loop optimization: AI recommends charging strategies (charge rate, SOC limits, temperature management), measure impact on degradation vs. control group. Build integrations with major fleet management systems (Geotab, Samsara, Verizon Connect) for seamless data ingestion. Develop residual value certification product: assess battery health for secondary market sales, partner with battery recyclers/repurposers. Achieve measurable outcomes: 20-25% battery life extension, $5K-$10K per vehicle in avoided replacement costs. Secure $2M ARR at $1,200/vehicle/year average. Raise $5M seed round on proof of unit economics and customer retention.

Phase 3

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Growth: Launch OEM licensing program: pitch battery management system integration to EV manufacturers. Value prop: reduce warranty costs (batteries are 30-40% of EV warranty expenses), differentiate on battery longevity claims in marketing. Target tier-2 and tier-3 EV manufacturers (Rivian, Lucid, Polestar, Chinese startups) who lack CATL/BYD's battery expertise. Develop insurance/warranty product: underwrite extended battery warranties using superior risk models, take 20-30% of premium as profit. Expand to energy storage systems (ESS): same degradation challenges exist in grid batteries, but with different use patterns. Build vertical-specific models for solar+storage, C&I applications. Reach $15M ARR with 70% from fleet SaaS, 20% from OEM licenses, 10% from warranty products. Raise $20M Series A to fund sales expansion and international growth.

Phase 4

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Moat: Achieve data network effects: with 50K+ vehicles and 100M+ charge cycles, prediction models become unbeatable. New competitors can't match accuracy without equivalent data. Build switching costs through deep integrations: fleet operators rely on Voltaic for maintenance scheduling, budgeting, and resale value optimization. Vertical integration into battery-as-a-service: offer subscription model where fleets pay per mile and Voltaic manages all battery costs (replacement, optimization, end-of-life). This captures full lifetime value and creates annuity revenue stream. Expand to adjacent markets: battery health certification for used EV sales (like Carfax for batteries), grid services (V2G optimization, frequency regulation), and battery passport compliance (EU regulation requiring lifecycle tracking). Strategic partnerships: co-develop next-gen BMS hardware with semiconductor companies (NXP, Infineon), integrate with charging networks (ChargePoint, EVgo) for optimized charging. Exit options: acquisition by automotive OEM seeking battery expertise, merger with fleet management platform, or IPO as battery intelligence layer for electrification. Defensibility comes from data moat, customer switching costs, and regulatory tailwinds (battery passport, right-to-repair, circular economy mandates).

Monetization Strategy

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Multi-sided revenue model capturing value across battery lifecycle: (1) Fleet SaaS: $50-200/vehicle/month subscription based on fleet size and features (basic health monitoring at $50, full optimization + predictive maintenance at $200). Target 50K vehicles by year 3 = $30M-$120M ARR. Gross margins 85-90%. (2) OEM Licensing: $5-15 per vehicle for BMS software integration, paid as royalty on vehicle sales. Target 5 OEM partnerships producing 200K vehicles/year by year 4 = $10M-$30M annual licensing revenue. Gross margins 95%. (3) Battery Warranty/Insurance: Underwrite extended warranties using superior risk models, charge 15-20% premium vs. traditional insurers, keep 25-30% as profit after claims. Target $50M in premiums by year 5 = $12M-$15M profit contribution. (4) Residual Value Certification: $200-500 per battery assessment for secondary market sales (EV-to-ESS repurposing, used EV sales). Target 20K assessments/year by year 4 = $4M-$10M revenue. Gross margins 80%. (5) Data Licensing: Anonymized battery performance data sold to battery manufacturers, researchers, and investors for $500K-$2M per dataset. Target $5M/year by year 5. (6) Transaction Fees: 3-5% take rate on battery replacement marketplace (connecting fleets with refurbished/new battery suppliers). Target $100M in GMV by year 5 = $3M-$5M revenue. Blended gross margins of 80-85% due to software-centric model. Customer acquisition cost (CAC) of $5K-$10K per fleet customer (enterprise sales), recovered in 6-12 months. LTV:CAC ratio of 8:1+ due to high retention (95%+ annual) and expansion revenue (upsells to premium tiers, additional vehicles). Path to $100M ARR by year 5 with 40% EBITDA margins, positioning for strategic acquisition at 10-15x revenue multiple ($1B-$1.5B exit) or IPO as category leader in battery intelligence.

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