Edge Computing for Energy & Utilities

The Energy & Utilities Sector — from mining to oil and gas — demands reliable, real-time insights in environments where connectivity is limited and conditions are extreme. Edge computing brings analytics closer to operations, enabling instant data processing, automation, and decision-making directly on-site.

At Edge Solutions Lab (ESL), we design resilient edge-to-cloud architectures that integrate ruggedized hardware, AI-powered analytics, and secure communication pipelines. Our systems operate reliably in remote or harsh conditions, using AI to analyze sensor data and provide actionable recommendations for faster, safer responses.

By running intelligence at the edge, ESL helps industrial operators minimize downtime, improve safety, and enhance operational efficiency — ensuring critical infrastructure runs smoothly, even when the network doesn’t.

energy edge computing - oil rig

Monitoring Worker Safety in Underground Mines with Edge Computing

Project Story

Challenge:
In underground and open-pit mines, operators lacked real-time visibility into workers’ health and location due to unstable connectivity and harsh conditions. Traditional methods like radios or manual check-ins couldn’t ensure continuous safety monitoring or fast response during emergencies. Dust, vibration, and humidity made standard IT systems unreliable underground.

Approach:
Edge Solutions Lab (ESL) developed an edge-powered safety monitoring system that operates reliably even without cloud connectivity. The solution included rugged wearable sensors that track heart rate, SpO₂, skin temperature, and activity, along with local edge servers that process and visualize data in real time.
The infrastructure was integrated with a partner’s specialized communication network, ensuring stable data transmission and instant alerts throughout the mine.

Solution & Results:
The system was piloted over 12 months at the Underground Mine Centre — a unique testing mine where leading mining companies validate new technologies under real-world conditions.

Key features included:

  • Certified wearable sensors designed for extreme mining environments
  • Local edge servers with high availability and fault tolerance
  • A real-time dashboard for worker health, activity, and location monitoring
  • Automated alerts for critical biometric or environmental parameters

The system maintained stable performance even without continuous internet access, giving supervisors real-time insights and enabling proactive responses to potential risks.

Impact:
The solution significantly improved worker safety, reduced medical incidents, and enhanced operational transparency. It also established a scalable edge platform adaptable for other high-risk industries — including energy, construction, and heavy industry — where reliability, autonomy, and data-driven safety are mission-critical.

Show more
ESL — experts in cloud-edge convergence

AI & Edge Orchestration for Oil Rig Optimization

Project Story

Challenge:
A U.S.-based oil and gas operator faced major data inefficiencies across its rigs. Thousands of sensors tracked pressure, viscosity, and flow rates — but limited hardware and bandwidth meant most data was never analyzed. Operators had to rely on intuition instead of real-time insights, while earlier “portable computing” attempts couldn’t handle full AI workloads or withstand harsh field conditions.

Approach:
Edge Solutions Lab (ESL) collaborated with the operator’s data team to enable on-site AI processing. Existing ML models for flow and anomaly detection lacked a deployment pipeline, so ESL designed a compact, fault-tolerant Edge AI infrastructure to run inference directly on the rig — reliable, low-maintenance, and resilient to vibration, heat, and poor connectivity.

Solution & Results:
ESL implemented a three-node Edge AI cluster with local orchestration and real-time data processing:

  • Instant ingestion and ML inference for pressure and flow optimization
  • Local data redundancy and secure synchronization
  • Compact, ruggedized setup embedded in the rig’s control unit

This architecture delivered real-time analytics at the edge, giving operators actionable recommendations for improving extraction efficiency.

Results:

  • On-site AI analytics with zero cloud latency
  • Stable operation in extreme conditions
  • Predictive pump control successfully deployed
  • Scalable design ready for multi-rig rollout

Impact:
The project proved how Edge AI transforms underused sensor data into real-time operational advantage — optimizing production, preventing incidents, and reducing downtime. It established a scalable model for deploying machine learning at the edge in demanding, bandwidth-limited environments

Show more
energy edge computing - oil rig

Why now?

It’s time to accelerate Cloud-to-Edge Convergence in Energy & Utilities!

As power grids and critical infrastructure become more digitized, processing data at the source has become essential. Cloud-to-Edge Convergence enables utilities to operate with greater reliability, efficiency, and resilience — especially where milliseconds matter and outages carry high risk.

Here’s why leading Energy & Utilities providers are embracing the edge right now:

5G rollout

5G rollout

5G drives the shift to the edge with the bandwidth and low latency needed for real-time grid insights, remote asset monitoring, and mobile workforce support. It also enables automated switching, line-fault detection, and fast integration of distributed energy resources.

Edge-specific compute acceleration

Edge-specific compute acceleration

Specialized processors (TPUs, NPUs, FPGAs) power on-site analytics for high-volume sensor data—from transformer thermal imaging to pipeline video and turbine vibration. They enable real-time anomaly detection, predictive maintenance, and faster decisions.

Mature edge platforms

Mature and utility-ready edge platforms

Lightweight orchestration tools and cloud-integrated platforms like K3s, AWS IoT Greengrass, Azure IoT Edge, and Google Edge TPU let utilities securely deploy apps across thousands of dispersed assets, simplifying management of rugged devices in remote substations, wind farms, solar arrays, and AMI/AMR endpoints.

Rise of edge-native applications

Growth of edge-native utility applications

New operational systems are being built for the edge—FLISR, real-time pipeline integrity monitoring, autonomous drone inspections, substation digital twins, and grid-edge DER/microgrid control—relying on instant local decisions that cloud-only setups can’t provide.

Standardization and interoperability

Standardization and interoperability

MQTT, OPC UA, gRPC, and open hardware/software standards are bridging legacy OT and modern IT, enabling smooth data exchange across SCADA, IoT devices, field sensors, and AI/ML systems—critical for multi-vendor utility environments.

On-device AI inference

On-device AI inference

Model compression and optimization now let AI run on field devices—from substation gateways to robots and smart meters. Local inference enables ultra-fast detection of faults, leaks, and overheating while reducing reliance on cloud connectivity in remote or harsh sites.

Let's Talk!

Ready to integrate the Cloud experience at the Edge of your grid, power plants, and utilities?

The Advantages of Edge Convergence for the Power, Energy & Utilities sector

We don’t just bring the Cloud to the Edge — we build intelligent, secure, and resilient edge infrastructure engineered for the demanding conditions of power grids, energy assets, and utility field environments.
Here’s why leading utilities and energy operators are moving to the Edge — and trusting us to guide the transformation:
Technical Advantages

Technical Advantages

Reduced Bandwidth Usage & Operational Costs.

Edge devices can filter, compress, or analyze sensor and equipment data locally before sending only what’s essential. This is especially valuable for high-volume sources such as substation cameras, pipeline video inspections, turbine vibration feeds, or AMI/SCADA telemetry — cutting network congestion and cloud storage costs dramatically.

Ultra-Low Latency for Critical Operations.

Grid protection, automated switching, DER orchestration, and real-time monitoring require decisions in milliseconds. Edge computing eliminates cloud round-trip delays, enabling faster fault detection, improved reliability, and safer autonomous operations.

Reliable Operation in Connectivity-Limited Environments.

Many energy assets — remote substations, offshore platforms, wind farms, solar fields, and transmission corridors — suffer from weak or intermittent connectivity. Our systems are built for autonomous, local operation, ensuring continuous functionality even when communications are unavailable for extended periods.

Improved Energy Efficiency & ESG Performance.

Processing data at the edge reduces the need to transmit raw telemetry to centralized data centers, lowering energy consumption across the entire architecture. This supports ESG goals by minimizing dependence on large, power-intensive cloud environments and favoring distributed, energy-optimized processing.

Freedom from Cloud Vendor Lock-In.

Modern, distributed edge architectures allow applications to run independently of any single hyperscaler or hardware vendor. This gives utilities flexibility, improves procurement leverage, and ensures long-term control over mission-critical systems that must operate for decades.
Privacy & Security Benefits

Privacy & Security Benefits

Data Sovereignty & Regulatory Compliance.

Edge computing supports compliance with sector-relevant standards and regulations — including NERC CIP, IEC 62443, GDPR, ISO 27001, and local utility governance requirements — by ensuring sensitive operational data stays within controlled geographic or jurisdictional boundaries. This is critical for grid telemetry, customer usage data, and infrastructure monitoring.

Enhanced Control Over Critical Operational Data.

By processing and storing information locally, utilities maintain full ownership and visibility over mission-critical data such as SCADA signals, transformer diagnostics, pipeline integrity logs, and substation video feeds. In many cases, cloud processing is restricted or prohibited due to the sensitivity of operational technology (OT) environments.

Reduced Attack Surface Across the Grid.

Minimizing data movement lowers the risk of interception, tampering, or leakage — especially across wide-area networks spanning transmission, distribution, and generation assets. Edge systems can be hardened further by disabling physical interfaces or enforcing strict OT cybersecurity controls.

Secure, Isolated, and Air-Gapped Environments.

Many energy sites require isolated, air-gapped, or tightly segmented networks to protect critical infrastructure. Edge deployments fit naturally into these architectures, keeping essential workloads secure, independent, and insulated from external threats or cloud outages.
Business & Operational Advantages

Business & Operational Advantages

Optimized Total Cost of Ownership (TCO).

By reducing dependence on centralized cloud services — especially for data-heavy workloads like substation video analytics, turbine monitoring, or pipeline inspection feeds — edge computing significantly lowers long-term operational costs and bandwidth requirements.

Autonomous Operation for Critical Infrastructure.

Edge systems continue performing essential functions even during network interruptions or cloud outages. This ensures uninterrupted operations across substations, generation sites, renewable installations, and remote field assets where reliability is non-negotiable.

Faster Operator and Field Team Experience.

Real-time responsiveness improves situational awareness and decision-making for control room operators, field crews, and inspection teams. Whether supporting digital twins, AR-assisted maintenance, or real-time equipment diagnostics, local processing delivers immediate insights.

Scalable Deployment Across the Grid.

Once validated at a single substation or plant, ESL edge architectures can be rapidly replicated across dozens or hundreds of sites — more efficiently and cost-effectively than centralized cloud-first models.

Site-Specific Customization.

Every energy site is different. Edge deployments can be tailored per substation, turbine, pipeline segment, plant unit, or microgrid — applying unique logic, AI models, or safety policies without affecting global operations.

Decentralized AI for Local Intelligence.

AI models may be trained centrally but are adapted and refined at the edge based on local conditions — enabling context-aware actions such as localized DER orchestration, predictive maintenance tuned to specific assets, and faster fault detection.

Flexible Financial Models (CAPEX vs. OPEX).

Unlike purely cloud-based platforms that enforce OPEX models, edge deployments can be structured as CAPEX, OPEX, or hybrid models — aligning with utility procurement rules, regulatory frameworks, and long asset lifecycles.

No Onsite IT Staff Required.

ESL edge systems offer centralized, cloud-like management with simple installation. Many edge devices can run autonomously for years with little physical intervention — ideal for remote substations, offshore platforms, and hard-to-reach transmission assets.

Low-Risk, Low-Cost Entry Point.

Our solutions support small-scale pilots at a single site or asset. Utilities can validate performance, cybersecurity, and operational value before rolling out edge systems across the broader grid or energy network.
Let's Talk!

Ready to explore how to bring the Cloud Experience to the Edge in your Power, Energy & Utilities project?

How it’s made? – Energy sector

Cloud-to-Edge Convergence in the Power, Energy & Utilities sector is a complex, multi-layered process that demands deep expertise across operational technology, rugged field hardware, and advanced software platforms. At Edge Solutions Lab, we guide utilities through every phase — from validating the use case to deploying edge systems across substations, plants, pipelines, or renewable assets, and supporting them throughout their lifecycle.
Here are the steps in our full-service approach, designed to ensure your Edge solution is resilient, scalable, and built for long-term operation in critical energy environments:
1 Platform Feasibility Study

Platform Feasibility Study for Power, Energy & Utilities

Our Platform Feasibility Study is the critical first step for any edge initiative in the Power, Energy & Utilities sector. At this stage, we analyze your operational needs, regulatory constraints, and long-term grid or asset strategy to determine whether an edge solution will deliver measurable value.

We perform a structured assessment of your existing OT and IT infrastructure — including substations, plants, pipelines, renewable assets, and control systems — and evaluate how well an edge architecture will integrate with your current cloud, SCADA, and data platforms. We also identify interoperability challenges, cybersecurity considerations, and operational risks before they become costly issues.

Based on these insights, we determine whether a deeper Discovery Phase is needed to define the full architecture, technology stack, and deployment roadmap across your grid or asset network.

The result is a clear, data-backed roadmap that aligns functionality, budget, compliance requirements, and scalability — ensuring you can move forward with confidence and a strong business case.

This phase ensures that what we build fits your operational goals, technical environment, regulatory needs, and financial constraints — while minimizing risk and maximizing ROI.

Find out more
Platform Feasibility Study
2 Hardware Design & Development

Hardware Design & Development for Power, Energy & Utilities Sector

From initial concepts to full-scale production, Edge Solutions Lab (ESL) delivers end-to-end hardware development services adapted for the demanding conditions of grid infrastructure, energy assets, and utility field operations. We design boards, modules, and rugged edge devices optimized for environments where performance, resilience, and energy efficiency are mission-critical.

Our expertise spans both electronics and mechanical design, including durable enclosures, industrial-grade mechanics, and full adaptation for mass production. We manage 3D prototyping, injection molding preparation, and thermal/cooling solution design to ensure every device is both field-ready and manufacturable at scale.

We work with trusted manufacturing partners in the USA, Germany, and Ukraine to deliver production at any scale — from pilot batches for substations or plants to large-volume manufacturing for widespread grid or asset deployments — all with strict quality control and compliance to energy-sector standards.

With our systematic end-to-end process — covering schematic development, PCB layout, prototyping, certification, and mechanical integration — you get hardware that meets today’s operational and regulatory requirements while anticipating future grid modernization needs.

Find out more
What is the Convergence of Edge Computing?
3 Firmware Development Services

Energy & Utilities Firmware Development Services

Firmware is the invisible but essential bridge between hardware and software, especially in mission-critical environments such as substations, generation plants, renewable assets, and pipeline or grid monitoring systems. At ESL, we build high-performance, field-ready firmware that powers embedded systems, utility IoT devices, industrial controllers, and AI-enabled edge platforms across the energy sector.

Our team delivers stable, secure, and optimized firmware tailored to your specific use case, operational constraints, and hardware architecture — ensuring reliable performance even in harsh or remote utility environments.

From low-level drivers and real-time control logic to communication stacks (MQTT, OPC UA, Modbus), cybersecurity features, and over-the-air update mechanisms, we ensure your devices operate safely, efficiently, and continuously in the field — unlocking their full potential while maintaining strict energy efficiency, security, and regulatory compliance.

Find out more
Edge Computing - Firmware Development Services
4 Software Design & Development

Software Design & Development for Power, Energy & Utilities

Great edge solutions in the energy sector require equally strong software. We combine architectural rigor with agile delivery to build applications that are efficient, scalable, and secure across generation, transmission, distribution, and renewable operations.

Our process includes requirements analysis, modular architecture design, iterative development, and long-term maintainability planning — ensuring every system is built to support the unique demands of OT/IT convergence, real-time processing, and grid reliability.

We follow a structured yet flexible approach that blends architecture planning with agile delivery cycles, ensuring software meets strict standards for performance, resilience, and scalability in distributed edge environments.

Whether you need cloud-native utility applications, hybrid platforms, embedded control logic, DER orchestration tools, or AI-driven predictive services, we ensure your software integrates seamlessly with your hardware, SCADA systems, IoT devices, and broader utility infrastructure — delivering dependable performance across edge deployments of any scale.

Whether you need Cloud-Native applications or Hybrid apps, embedded logic, or AI-driven services, we ensure that the software integrates tightly with your hardware and infrastructure — delivering dependable performance across edge deployments of any scale.

Find out more
Edge Computing - Software Design & Development
5 Hardware–Software Integration

Hardware–Software Integration for Power, Energy & Utilities

In the Power, Energy & Utilities sector, the performance and reliability of edge computing systems depend on how efficiently hardware and software work together. At Edge Solutions Lab (ESL), we specialize in deep hardware–software integration, covering every layer from BIOS and firmware to real-time operating systems, SCADA interfaces, and edge application logic.

By testing and optimizing across the full technology stack, we reduce latency, lower power consumption, and ensure stable, continuous operation in demanding environments such as substations, generation facilities, renewable sites, and pipeline monitoring systems.

This holistic, energy-sector–focused approach guarantees that your edge systems operate exactly as intended — reliably, efficiently, and with the performance and resilience required for critical infrastructure.

Find out more
Edge Computing - Hardware–Software Integration
6 DevOps at Edge Solutions Lab

DevOps for Power, Energy & Utilities at Edge Solutions Lab

In the Power, Energy & Utilities sector, deployment is not just about launching code — it’s about creating a repeatable, automated, and secure operational environment that can scale across substations, generation sites, pipelines, and renewable assets.

Our team brings deep expertise in Infrastructure as Code (IaC) using Ansible and other modern DevOps tools, ensuring scalable, auditable, and repeatable automation across both edge and cloud environments.

We specialize in automating the deployment, configuration, and scaling of distributed edge systems — enabling faster rollouts, consistent configurations, stronger security postures, and reduced operational overhead for mission-critical energy infrastructure.

Find out more
Edge Computing - Software Design & Development
7 AI & LLM Deployment at the Edge

AI & LLM Deployment at the Edge for Power, Energy & Utilities

Deploying AI, LLMs, and advanced edge applications in the Energy & Utilities industry requires overcoming unique challenges — including limited bandwidth, harsh field conditions, regulatory constraints, and diverse hardware across substations, plants, pipelines, and renewable sites. This work demands tight collaboration between DevOps engineers, OT/IT teams, and application developers.

We build robust deployment pipelines that automate the distribution, updates, and monitoring of edge applications — even in remote, air-gapped, or resource-constrained environments typical in energy infrastructure.

For AI workloads, including predictive models, LLMs, and computer vision, we ensure models are optimized, validated, and continuously updated to maintain high accuracy, performance, and cybersecurity.

With our approach, your applications and AI services run reliably where they matter most — at the grid edge, close to the data, enabling faster insights, safer operations, and smarter decision-making.

Find out more
What is the Convergence of Edge Computing?
8 Hardware & Software Validation

Hardware & Software Validation for Power, Energy & Utilities

Validation is about trust — trust that your system will operate exactly as intended in the demanding, real-world conditions of substations, generation plants, renewable assets, and pipeline or grid monitoring environments. We design multi-layered testing frameworks that range from component-level checks to full system stress tests.

Our validation pipelines cover functionality, performance, resilience, and regulatory compliance, ensuring that both hardware and software can withstand the operational demands of critical energy infrastructure. By integrating testing into every phase of development, we reduce risks, accelerate certification, and deliver a reliable edge platform ready for deployment at scale.

Testing is not a final step — it’s an integral part of the entire product lifecycle. From initial prototype validation to fully automated test suites, every component is tested, tracked, and proven to meet the standards required for long-term operation in the Power, Energy & Utilities sector.

Find out more
Edge Computing - Hardware & Software Validation
9 Seamless Edge Scaling

Seamless Edge Scaling for Power, Energy & Utilities

Scalability is one of the largest challenges in deploying edge computing across the power grid, energy assets, and utility field operations — and ESL makes it achievable. We design scalable edge platforms that let you replicate, configure, and deploy entire edge environments like templates across hundreds or thousands of substations, plants, renewable sites, or pipeline segments.

Our solutions enable fast, predictable expansion by providing pre-validated deployment processes, centralized management, and automated configuration, ensuring that every new site can be brought online without redesigning the system from scratch.

Instead of rebuilding your architecture for each location, you get a streamlined path to growth — from pilot deployments to fleet-wide or grid-wide rollouts. ESL transforms your edge solution into a scalable, repeatable platform: deploy once, then scale as your grid and operations grow.

Find out more
Edge Computing - Hardware–Software Integration
10 Smart, Automated Maintenance

Smart, Automated Maintenance at Scale for Power, Energy & Utilities

Maintenance for critical energy infrastructure shouldn’t be reactive — it should be proactive, predictive, and automated. Our approach integrates monitoring, updates, and issue resolution directly into CI/CD pipelines, enabling large-scale edge deployments across substations, generation plants, renewable assets, and pipeline networks to be maintained with minimal human intervention.

From remote diagnostics and automated firmware updates to secure software rollouts and continuous health monitoring, we ensure your edge systems remain secure, up to date, and fully operational — without service interruptions or site visits.

We design edge platforms to support fleet-wide maintenance, allowing utilities to execute simultaneous updates, real-time monitoring, and automated issue resolution across distributed assets — all while keeping the grid and operations running smoothly.

With Edge Solutions Lab (ESL), maintenance becomes a strategic advantage, strengthening system reliability, reducing operational overhead, and keeping your critical energy infrastructure healthy at scale.

Find out more
Edge Computing - Hardware & Software Validation
Let's Talk!

Ready to explore how to bring the Cloud Experience to the Edge in your project?

Is Cloud-to-Edge Convergence Right for You?

Here’s what you need to do to Find Out
Bringing the Cloud Experience to the Edge can transform how your systems operate — but like any strategic investment, it should be guided by clear business and technical needs. To understand whether Cloud-to-Edge Convergence is right for your organization, follow these key steps:
1

Identify Your Use Case & Constraints

Start by defining the operational scenarios where real-time processing, reduced latency, offline functionality, or data privacy are critical.

Common examples include remote monitoring, AI inference in the field, industrial control systems, or secure data handling at the Edge.

2

Assess Existing Infrastructure

Evaluate your current hardware, connectivity, software architecture, and data flow.

Are your systems centralized and cloud-dependent? Do you face issues with latency, bandwidth costs, or downtime? This helps highlight where Edge Computing could create immediate value.

3

Evaluate Scalability & Future Growth

Ask yourself: Will your operations scale across locations, devices, or regions?

Edge architecture allows you to “deploy once, replicate everywhere” — which is ideal for multi-site businesses or distributed assets.

4

Consider Compliance, Security & Control Need

If you operate in a regulated industry (e.g., healthcare, defense, telecom), Edge Computing helps keep sensitive data local, meet residency laws, and reduce attack surfaces — making it a strategic advantage.

5

Talk to an Expert

Finally, consult with the Edge Solutions Lab team. We’ll help you assess feasibility, estimate ROI, and determine the most effective way to design and deploy an Edge-native architecture tailored to your needs.

Let’s find out if Edge is the right fit — and what it could mean for your future

The sooner you evaluate your Edge readiness, the faster you can unlock faster response times, smarter automation, and scalable digital operations.

Let’s Talk!

Frequently Asked Questions

What is edge computing in the energy sector?

Edge computing in the energy sector involves the processing and analysis of data in proximity to its source of generation, such as power plants or smart meters. This approach facilitates real-time monitoring of energy flows and significantly enhances decision-making processes in energy management. As a result, it enables utilities to optimize their operations and improve grid stability.

How can edge computing benefit the energy industry?

The benefits of edge computing in the energy industry include improved efficiency and reliability. By leveraging edge computing solutions, utilities can manage distributed energy resources more effectively, balance energy supply and demand, and enhance the integration of renewable energy sources into the power grid.

What role does edge intelligence play in energy management?

Edge intelligence enables advanced analytics and decision-making capabilities at the edge of the network. In energy management, it allows for the real-time analysis of energy data, helping utilities to predict power flow and address power quality issues swiftly, ultimately leading to more sustainable energy operations.

How does edge computing optimize renewable energy integration?

Edge computing optimizes renewable energy integration by facilitating real-time monitoring and management of energy generation from renewable energy sources. It helps utilities to efficiently integrate these resources into the grid, ensuring a reliable energy supply while supporting the transition to clean energy.

What are the applications of edge computing in the power grid?

Applications of edge computing in the power grid include real-time energy monitoring, predictive maintenance of grid infrastructure, and enhanced management of energy storage systems. These applications help utilities improve grid resilience and respond proactively to changes in energy demand and supply.

Can edge computing improve electricity reliability?

Yes, edge computing can significantly improve electricity reliability by enabling real-time data processing and analysis. This allows utilities to quickly identify and resolve issues related to power quality and grid stability, ensuring that customers receive consistent and reliable energy.

How is edge computing transforming the energy market?

Edge computing is transforming the energy market by enabling smarter energy distribution and enhancing the efficiency of energy management systems. With the increase in distributed energy resources, utilities can better manage the energy landscape, adjusting to fluctuations in energy prices and demand more effectively.

What are the challenges of implementing edge computing in energy operations?

Challenges in implementing edge computing in energy operations include the need for robust computing resources at the edge, ensuring cybersecurity, and integrating new technologies with existing infrastructure. Utilities must also address the complexities of managing real-time data across diverse energy networks.

How does edge computing support the energy transition?

Edge computing supports the energy transition by enabling the integration of clean energy technologies and enhancing energy management capabilities. By providing real-time insights and optimizing energy operations, utilities can accelerate the shift towards more sustainable energy practices and the adoption of electric vehicles.

Let's Talk!
Ready to explore how to bring the cloud experience to the edge in your project?