The AI-Powered Operating System for Energy and EV Infrastructure Orchestration
Kazam has emerged as a dominant force in the 2026 energy landscape, providing a sophisticated AI-IoT platform that orchestrates the complex interplay between electric vehicles, charging infrastructure, and the power grid. Its technical architecture centers on 'Kazam Data Lab,' which utilizes advanced machine learning models to solve the stochastic nature of energy demand. By leveraging proprietary computer vision (OCR) to digitize analog energy meters and neural networks for State-of-Health (SOH) battery diagnostics, Kazam provides an end-to-end stack for fleet operators and utility providers. The platform's 2026 market positioning is focused on 'Grid-to-Vehicle' (G2V) and 'Vehicle-to-Grid' (V2G) optimization, allowing enterprises to turn charging stations into active grid assets. Its microservices-based architecture supports OCPP 2.0.1 protocols and integrates seamlessly with legacy ERP systems, making it the technical benchmark for scalable green-energy infrastructure.
A sandbox for running custom ML models against real-time IoT telemetry for specific site optimizations.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Uses LSTM (Long Short-Term Memory) networks to predict building load and adjust EV charging output in milliseconds.
Edge-AI OCR that interprets analog and digital electricity meter displays via standard smartphone cameras.
Middleware that translates between disparate hardware protocols to a unified Kazam-standardized JSON output.
ML algorithms that analyze voltage drop and charging curves to estimate battery degradation over time.
Blockchain-integrated ledger that converts verified green energy charging into tradeable carbon offsets.
Real-time API integration with utility dispatch centers for automated frequency response and demand-side management.
Preventing circuit breaker trips when 50+ employees plug in EVs simultaneously during work hours.
Registry Updated:2/7/2026
System alerts facility manager if demand exceeds safety thresholds.
Ensuring all delivery vans are 100% charged by 6:00 AM while minimizing cost.
Managing a multi-brand charger network with complex billing for different user groups.