Sigenergy expands AI-powered energy management globally
Learn how Sigenergy, an energy storage company, built its intelligent energy platform on AWS to scale securely across global markets.
Benefits
- faster market go-live
- 70%
- countries and regions served
- 80+
- faster fault diagnosis
- 70%
- global platform uptime
- 99.9%
Overview
As Sigenergy expanded its integrated AI, solar-storage-charging solutions to more than 120 countries and regions, it needed to support varying data compliance and cybersecurity requirements while managing more than 400,000 connected devices. With AWS, Sigenergy built a multi-Region cloud foundation for localized data storage, compliant operations, and global platform reliability. It also deployed AI capabilities across customer service, energy platforms, fault diagnosis, forecasting, personalized energy management, and R&D efficiency. The company reduced new Region launch time from 4–6 weeks to 1–2 weeks, cut fault diagnosis time by 60–70 percent, and maintained 99.9 percent uptime.
Opportunity
Addressing two critical challenges in global expansion
Since its founding in 2022, Sigenergy has achieved a compound annual growth rate (CAGR) exceeding 100 percent. By 2026, the company’s products and services had reached more than 120 countries and regions worldwide, with more than 400,000 connected devices. Amid this rapid growth, Sigenergy faced two key challenges as it expanded globally and advanced its intelligent transformation.
The first challenge was compliance. Countries have varying regulatory requirements for data privacy, cybersecurity, and grid access. The European Union enforces the General Data Protection Regulation (GDPR), Australia mandates localized data storage, and certification frameworks differ across regions. As Sigenergy expanded internationally, compliance, cybersecurity, and data residency requirements became increasingly complex. Each market had distinct regulatory frameworks and security expectations, requiring Sigenergy to embed compliance into its cloud architecture and operating model from the outset, rather than retrofit its approach for each country or region on a case-by-case basis.
“We needed to design our platform architecture for global operations from day one. As we entered new markets, we wanted foundational infrastructure that could help us scale quickly while supporting diverse compliance, security, and customer requirements,” says a representative from Sigenergy’s Cloud Platform Team.
The second challenge was intelligent operations. With over 400,000 devices distributed worldwide, traditional manual troubleshooting processes were inefficient and slow. Electricity pricing policies, grid structures, and weather conditions varied by country, making fixed-strategy energy management insufficient. Customers expected the system to automatically learn the optimal times to charge and discharge, rather than rely on manual parameter adjustments. Meanwhile, customers in more than 120 countries required multilingual, real-time technical support, a need that traditional customer service models struggled to meet.
Solution | Architecting a global platform for intelligent energy services
Sigenergy chose AWS as the cloud foundation for its global intelligent energy platform, helping the company scale digital energy services and AI-driven energy management across multiple markets.
Global unified standards, regionally adapted implementation
Sigenergy embeds compliance capabilities into its platform architecture from the design phase. The company uses a cloud-native “one codebase, multi-Region deployment” model, enabling more systematic security and governance. With AWS, Sigenergy integrates network boundaries, application protection, key management, credential management, log monitoring, and security auditing into a unified governance framework, reducing the management complexity associated with rapid expansion.
To improve operational transparency and support data-informed customer service and operations and maintenance (O&M), Sigenergy uses Amazon CloudWatch for monitoring, alerting, and observability across its platform environment. With Amazon OpenSearch Service, Amazon Simple Email Service (Amazon SES), and other services, its customer service and O&M teams can quickly access operational status, log information, alert notifications, and service context, accelerating issue identification and cross-team collaboration.
To support secure network connectivity and application protection, Sigenergy uses Amazon Virtual Private Cloud (Amazon VPC), AWS Direct Connect, and AWS WAF. These services help the company define network boundaries, support private connectivity, and strengthen application-layer protection across its global platform environment.
For identity and access management, Sigenergy implements role-based access controls for internal R&D, O&M, customer service, regional teams, installers, and partners, helping ensure that each role can access only the data and features within its scope of responsibility. Sigenergy uses AWS Key Management Service (AWS KMS) for key management and AWS Secrets Manager to manage database passwords, API tokens, certificates, and other sensitive credentials, reducing the risk of plaintext credential exposure across R&D and O&M workflows.
At the regional level, Sigenergy selects data storage locations based on each country’s regulatory requirements. The company currently operates six data center nodes globally, covering Europe, Asia Pacific, Australia, and other regions, with user data stored in the respective regions to meet data localization requirements.
Four scenarios demonstrating the capabilities of an AI-native smart energy platform
Building on its compliance foundation, Sigenergy uses AWS to deploy AI capabilities across four core scenarios: site-wide intelligent forecasting, personalized closed-loop energy management solutions tailored to individual users, intelligent customer service and AI assistants, and enhanced R&D efficiency. The first three scenarios address user experience, intelligent dispatch, and service diagnostics, while the fourth demonstrates how AWS and Kiro support engineering efficiency and continuous innovation.
Scenario 1: Site-wide intelligent forecasting
Forecasting is the foundation of intelligent energy management. Sigenergy is expanding photovoltaic (PV), load, and state-of-charge (SOC) forecasting from selected scenarios into a platform-wide capability available across all sites. This helps users understand generation, load, and battery trends in advance. They can then manage electricity usage more proactively, such as by avoiding peak tariff periods, adjusting when high-power equipment operates, increasing self-consumption, or reserving backup power.
With support from AWS, Sigenergy builds forecasting and optimization models using Amazon SageMaker, incorporating layered strategies such as periodic forecasting, result caching, and real-time API calls to reduce redundant computation as the number of sites scales. Amazon Elastic Kubernetes Service (Amazon EKS) and Amazon Elastic Compute Cloud (Amazon EC2) support business logic and service workflows, while Amazon CloudWatch and Amazon OpenSearch Service provide monitoring and troubleshooting capabilities. Forecasting results also feed into energy flow visualizations and AI-driven dispatch strategies, helping users understand not only what happened, but also what is likely to happen next and why the system schedules energy in a certain way.
Scenario 2: Personalized energy management closed-loop solutions tailored to individual users
Different users have different energy management goals, such as maximizing self-consumption, reducing electricity bills, optimizing returns, or prioritizing backup power availability. On AWS, Sigenergy has built a smart energy management system that connects user goals, personal preferences, forecasts, strategy execution, and feedback, helping ensure that dispatch strategies align with each user’s expectations.
Leveraging AWS services such as Amazon Bedrock, Amazon SageMaker, Amazon Key Management Service (Amazon KMS), and AWS Secrets Manager, Sigenergy enables users to select their preferred energy mode and set personalized preferences in mySigen. The platform then generates and executes energy strategies based on dynamic electricity pricing, photovoltaic (PV), load, and state-of-charge (SOC) forecasts, device configurations, and user preferences. After execution, AI explains why the system charged or discharged energy, provides insights into dispatch decisions, and shows the impact on energy costs and returns. Users can then refine their preferences, creating a continuous cycle of optimization, explanation, and feedback.app
Scenario 3: Intelligent customer service and AI assistant
Sigenergy’s intelligent customer service and AI assistant capabilities go beyond simple knowledge base queries, helping users, installers, and service teams diagnose issues and manage operations more efficiently. Users can query system status using natural language, understand the causes of alarms, and receive configuration recommendations. Service teams can also identify issues faster by correlating device data, product documentation, and ticket history.
Sigenergy built this capability using Amazon Bedrock, enabling knowledge base Q&A, automated ticket classification, fault diagnosis recommendations, and multilingual understanding. For common issues, the system provides structured solutions to improve first-contact resolution rates. For complex faults, it analyzes alarm context by connecting knowledge bases, data queries, and operational tools, then provides targeted troubleshooting recommendations.
Using Amazon Bedrock, Amazon OpenSearch Service, and Amazon CloudWatch, the AI assistant can also connect to forecasting capabilities, dispatch strategies, device status, and operational logs to explain scheduling logic and the impact on returns. This extends its role beyond customer service Q&A to support energy management and fault diagnosis, delivering a consistent and efficient support experience for customers and service teams worldwide.
Scenario 4: R&D efficiency enhancement
Sustaining AI innovation also depends on R&D efficiency. Sigenergy uses tools such as Kiro to improve engineering productivity, supporting code understanding and generation, cloud resource analysis, issue troubleshooting, and architecture recommendations. These tools also help translate requirements into specifications, code, documentation, and tests, reducing repetitive engineering work.
As the global platform continues to evolve, greater R&D efficiency helps the team respond more quickly to multi-Region compliance needs, business changes, and platform stability demands. Combined with AWS cloud infrastructure, observability capabilities, and AI toolchains, Sigenergy is building a more efficient connection between product innovation, issue identification, and engineering delivery. This provides the engineering foundation to deploy AI capabilities across more markets and scenarios.
Platform infrastructure
Beyond the two core pillars of compliance and AI, Sigenergy’s global platform also relies on the following AWS services: Amazon EC2 and Amazon EKS run core workloads, providing the compute and container orchestration capabilities needed to deliver stable services to customers and service teams worldwide.
The platform also uses Amazon Elastic Container Registry (Amazon ECR) and services such as Amazon EC2 and Elastic Load Balancing, to support application operations, traffic distribution, network connectivity, and global access. Amazon OpenSearch Service supports log retrieval and full-text search. For notification delivery, Sigenergy uses Amazon SES to send system, notification, and service-related emails, supporting email delivery worldwide
These services work alongside Sigenergy’s broader AWS foundation to support scalable application operations, network connectivity, operational visibility, and notification delivery worldwide.
“AWS provides us with reusable cloud infrastructure. We don’t need to redesign our infrastructure from scratch every time we enter a new market, launch a new service, or roll out a new deployment,” says a representative from Sigenergy’s Cloud Platform Team.
Outcome
Reducing new-market go-live time by up to 70%
Sigenergy reduced new-region go-live time from 4–6 weeks to 1–2 weeks, helping the company expand its intelligent energy services over 120 countries and regions. Its AWS-based platform also maintains 99.9 percent uptime globally while supporting cross-region data synchronization latency below 100 milliseconds and large-scale device connectivity.
Using Kiro for AI-assisted development, Sigenergy improved code review efficiency by 40 percent and reduced unit testing time by more than 50 percent. The company also increased knowledge base retrieval efficiency by more than 70 percent, helping teams access technical information more efficiently across global operations.
AI-enabled diagnostics also improved customer support responsiveness. Sigenergy reduced fault diagnosis times for connected energy storage systems by 60–70 percent, while first-time resolution rates improved to more than 80 percent.
For customers, Sigenergy’s intelligent energy management capabilities help optimize electricity usage and storage strategies based on pricing, weather conditions, and energy demand. In the United Kingdom, these capabilities helped improve monthly customer revenue by 22 percent, while customers in Poland reduced total energy costs by 52 percent.
“With AWS, we can scale global energy services more efficiently while maintaining reliable operations across rapidly expanding markets,” says a representative from Sigenergy's Cloud Platform Team.
Future outlook
Going forward, Sigenergy aims to deepen its collaboration with AWS while evolving its smart energy platform from device management toward an autonomously optimizing energy operating system. With AWS as a foundation for global replication and continuous iteration, Sigenergy can continue extending AI capabilities across real-world energy management scenarios, including generative AI assistants, predictive model engineering, intelligent dispatch, VPPs, and cross-Region compliance operations.
With AWS, we can scale global energy services more efficiently while maintaining reliable operations across rapidly expanding markets.
Representative, Cloud Platform Team, Sigenergy
About Sigenergy
Founded in 2022 and headquartered in Shanghai, Sigenergy develops AI-powered photovoltaic (PV), energy storage, and electric vehicle (EV) charging solutions. Guided by its "AI in All" strategy, the company integrates AI across its products to deliver intelligent energy management for households and businesses worldwide.
AWS Services Used
Disclaimer: Amazon Web Services currently deploys the aforementioned certain generative AI-related services in Global regions. Amazon Web Services China region services are operated by NWCD and Sinnet, with more details at the official Amazon Web Services China region website.
