Alchemy Charge consulted with SoSavvy to bring their proprietary EV Charging platform to market, delivering a full-stack solution including cloud, web, and mobile applications to manage EV charging stations across Australia.
Alchemy Charge partnered with SoSavvy to deploy a robust EV charging network platform, capable of scaling from a pilot to a full nationwide rollout across strata buildings, short-stay rentals, and commercial parking hubs. By integrating cloud-native microservices, OCPP 2.x charge point interoperability, and dynamic billing engines, the solution supports real-time session management, load balancing, and user authorisation.
Modular Cloud Architecture & Microservices
The backend leverages a modular architecture running on AWS — including isolated services for session control, pricing, user accounts, and telematics ingestion. Each charge point communicates via conformant OCPP protocols over secure WebSockets, forwarding meter data, diagnostics, and firmware versioning. The architecture adopts a serverless event-driven core using AWS Lambda, SQS, and DynamoDB to ensure elasticity and fault isolation.
Intelligent Load Management & Grid Awareness
Alchemy's system dynamically allocates charging current across multiple points using predictive load models and real-time utility signals. The platform supports scheduled sessions, flexible power throttling, and demand-response control in response to grid constraints or peak pricing. During high-demand events, adaptive algorithms reduce power draw gracefully to maintain safe operation under local supply limits.
User Experience & Ecosystem Integration
The mobile frontend offers seamless onboarding, live session tracking, usage analytics, and QR-based plug authorisation. For strata and property managers, a unified dashboard supports bulk device registration, firmware orchestration, and fault reporting. Integrations with billing APIs, ERP systems, and energy markets ensure a plug-and-play utility for large-scale deployment.
Continuous Metrics & Improvement
Crucially, Alchemy and SoSavvy established a feedback loop: charger telemetry, historical demand, and user behavior feed back into machine-learning models that fine-tune pricing thresholds, power distribution policies, and failure detection heuristics. Over the initial deployment, system-wide uptime exceeded 99.7%, response latency stayed under 100 ms for control commands, and mean time to failure (MTTF) increased by 18 %.
Pay-Per-Use power point for EV Charging, Designed for Strata Buildings, Short Term Rentals and Car Parks