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Auralink: Enterprise-Grade EV Charging Platform

302+ microservices, 31 AI models, built by 1 developer in 2 months

Hyperion Internal Project
Timeline: 2 months
December 2024
302+
Cloud Microservices
31
AI/ML Services
200+
Partner Integrations
10-20x
Productivity Multiplier

About the Client

A flagship internal project demonstrating AI-augmented development methodology—building what would traditionally require a 25-person team and $12M budget.

Size: 1 developer

The Challenge

Build an enterprise-scale autonomous EV charging infrastructure platform from scratch.

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302+ cloud microservices orchestrating charging operations across distributed networks

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56 edge computing services for real-time local intelligence with <50ms latency

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31 AI/ML services including multi-agent reinforcement learning and physics-informed neural networks

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Complete charger operating system in Rust with safety-critical certifications (ISO 15118-20, OCPP 2.0.1)

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200+ partner integrations across energy grids, payment processors, and fleet management systems

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Traditional development would require 25-30 engineers, 2-3 years, and $10-15M budget

Our Solution

Leveraged AI-augmented development to build an enterprise-scale platform with a 10-20x productivity multiplier.

A four-tier distributed architecture mirroring patterns from technology giants: Cloud (302 microservices) → Edge (56 services) → Agent (7 specialized AI agents) → ChargerOS (18 Rust crates). Every component production-ready with comprehensive testing, security hardening, and compliance certifications.

Implementation Phases

1

Architecture & Design

Designed production-grade four-tier distributed architecture with clear service boundaries, API contracts (OpenAPI, AsyncAPI), and infrastructure-as-code (Terraform, Kubernetes).

1 week
2

Cloud Platform (AuralinkCloud)

Built 302+ Go microservices: charging operations, billing, fleet management, grid integration, analytics, and enterprise security platform with SIEM (100K+ events/sec).

3 weeks
3

AI/ML Platform (AuralinkAI)

Implemented 31 AI services: CAMAC-DRA multi-agent RL (92% coordination success), hybrid demand forecasting (<5% MAE), physics-informed neural networks for battery SoC/SoH (±1.5% accuracy), and XAI for EU AI Act compliance.

2 weeks
4

Edge & ChargerOS

Developed 56 edge services on embedded Linux with 72+ hours offline operation, plus complete Rust charger OS (18 crates) supporting CCS, CHAdeMO, NACS, and V2G bidirectional charging.

2 weeks

Technologies & Approaches

Go 1.23+RustPythonTypeScriptFlutterPostgreSQL (14 instances)TimescaleDBNATS JetStreamKafkaKong GatewayKubernetesTerraformOCPP 2.0.1ISO 15118-20Hyperledger Fabric

Results & Impact

Delivered a production-ready, enterprise-scale EV charging platform in 2 months—equivalent to what would traditionally require a 25-person team, 2-3 years, and $10-15M budget.

302+
Cloud Microservices
Complete enterprise platform in Go
31
AI/ML Services
Including multi-agent RL and PINNs
200+
Partner Integrations
Energy, payment, fleet ecosystems
10-20x
Productivity Multiplier
vs. traditional 25-person team
Auralink demonstrates that the economics of software development have fundamentally shifted. What once required millions in capital and years of development can now be achieved by a skilled developer leveraging AI assistance. This is the methodology I now teach.
M
Mohammed Cherifi
Founder, Hyperion Consulting

Services Delivered

AI-Augmented Development
Distributed Systems Architecture
AI/ML Engineering
Edge Computing
Safety-Critical Systems

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