Wildfires are no longer confined to the western United States. In 2025 alone, the U.S. experienced more wildfires from January to August than in any comparable period over the past decade. These fires are increasingly ignited by grid-related failures, loose hardware, vegetation contact, and aging infrastructure – posing a growing threat to utilities nationwide. As climate change intensifies and regulatory scrutiny increases, utilities must shift from reactive inspection models to proactive, data-driven wildfire mitigation strategies. 

A recent industry webinar brought together experts from eSmart Systems, Microsoft, Technosylva, and the Smart Electric Power Alliance (SEPA) to explore how artificial intelligence (AI) and predictive insights are helping utilities stay ahead of wildfire risks. The core of the discussion was how digital twin technologies, AI-powered inspection platforms, and predictive analytics are redefining the way utilities inspect, manage, and protect their infrastructure. 

The Expanding Wildfire Threat 

“Wildfire risk is no longer a regional concern,” said Don McPhail, VP of Market Development at eSmart Systems. “Utilities in areas that haven’t traditionally faced wildfires are now seeing increased threats due to hotter temperatures, prolonged droughts, and vegetation growth.” 

Jared Leader from SEPA echoed this sentiment, noting that even utilities in Virginia and the Midwest are developing wildfire mitigation plans. “Having a wildfire plan is not optional anymore,” he said. “It’s central to utility planning.” 

The stakes are high. Lives, infrastructure, and billions of dollars in liability are on the line. And with federal funding, such as the $3.7 billion wildfire initiative, now supporting AI adoption and data-sharing frameworks, utilities have a unique opportunity to modernize their approach. 

Digitalization: The Foundation of Proactive Risk Management 

At the heart of this transformation is digitalization. By creating a digital representation of your grid (image-based database that integrates high-resolution imagery, asset metadata, and grid topology and it’s all centralized in one place), utilities gain near real-time visibility into asset health and environmental conditions. 

“Digitalization isn’t just the first step, it’s the bare minimum,” said Bilal Khursheed, Executive Director for Power & Utilities at Microsoft. “You can’t manage what you can’t measure.” 

This visibility enables utilities to detect vegetation encroachment, asset degradation, and environmental stressors, supporting predictive analytics that identify risks before they escalate into ignition events. 

AI-Powered Inspections: Faster, Smarter, Safer 

Traditional inspections are slow and labor-intensive. A single inspector climbing lattice towers could take years to complete a full inspection cycle. In contrast, drone-assisted inspections combined with AI-powered image analysis can reduce that timeline by up to 80%. 

In one case study, a North American utility inspected 47 lattice towers and 52 wooden poles, capturing over 3,400 images.  
 
The AI detected: 

• 781 upside-down cotter pins 
• Loose shackles and contaminated insulators 
• Anomalies like woodpecker holes and cracked poles 

These insights allowed the utility to target repairs that target high risk of ignition sources without climbing towers, improving safety and reducing risk. “We’re seeing a 60% uplift in defect detection compared to traditional methods,” McPhail noted. 

Predictive Insights and Vegetation Management 

Beyond defect detection, AI enables predictive insights by analyzing historical data and identifying patterns. For example, wooden poles near water may degrade faster due to humidity, while certain asset classes may show recurring vulnerabilities. 

Vegetation is a primary fuel source for grid-related fires. AI-powered platforms use high-resolution imagery combined with conditional data to monitor vegetation encroachment and assess the overall health of grid assets. “Risk is everywhere and constantly changing,” said Indran Ratnathicam, Chief Growth Officer at Technosylva. “It’s not about knowing if your risk is high or low—it’s about knowing where and when it is.”

Human Expertise + AI: A Collaborative Future 

While AI is a powerful tool, the panel emphasized that it’s not a replacement for human expertise. “AI augments decision-making,” said Khursheed. “It gives field crews superpowers, not pink slips.” 

McPhail added, “The real transformation happens when data becomes insight, and insight becomes action. That’s where AI fits into the workflow, not as a standalone tool, but as part of a broader strategy.” 

Advice for Utilities Starting Their AI Journey 

AFor utilities just beginning to explore AI, the panel offered clear guidance: 

• Start now. “The best time to plant a tree was 10 years ago. The second-best time is now – the same applies to utilities’ AI journey” McPhail said. 
• Standardize and centralize data. Structured, high-quality data is essential for effective AI. 
• Think beyond pilots. “Proof of concept proves potential, not readiness,” said Khursheed. Scaling requires operational integration. 
• Collaborate. Partnering with experienced technology providers ensures success under real-world conditions. 

A Call to Action 

Wildfires are a growing crisis, but AI-powered inspection platforms and predictive analytics offer a path forward. By digitalizing assets, leveraging predictive insights, and integrating vegetation management, utilities can move from reactive to proactive wildfire mitigation. 

As McPhail concluded, “Don’t wait for a fire to force change. Embrace AI and data-driven tools now. The cost of inaction is far greater than the investment in proactive technology.” 

November 2025 – eSmart Systems has launched Verify AI, the first feature powered by its new and patent pending Adaptive AI technology. This advancement accelerates how utilities transform asset data into trusted insights that support safe and reliable grid operations.

Traditional AI has already improved digital inspection workflows. However, utilities still face high volumes of false positives, long deployment timelines, and difficulty tailoring results to local power grid requirements. These challenges impact decision-making and risk management.

Adaptive AI introduces a step change by enabling rapid value from limited or uneven training data. It adapts to each utility’s power grid and standards with minimal effort and improves continuously based on expert feedback.

Verify AI is the first feature based on Adaptive AI and is now available in the Grid Vision^® platform. Verify AI strengthens inspection workflows by reducing false positives and elevating only credible issues for review. This creates faster, more trusted results and allows inspectors and asset managers to focus on what matters most.

Adaptive AI will support additional features over time, including new defect detection and inventory capabilities, all designed to scale utility intelligence and improve operational outcomes.

Key benefits include:

• Faster deployment and value realisation
• Reduction in false positives and manual review effort
• Trusted insights aligned to each utility’s standards
• Stronger risk mitigation and prioritisation of critical work

Verify AI is available today in Grid Vision^®. More features powered by Adaptive AI will be released in upcoming product iterations.

About eSmart Systems

eSmart Systems is a global leader in AI-powered solutions for the inspection, analysis, and digitalization of critical grid infrastructure. Through our Grid Vision^® platform, we help utilities transition from manual inspections to intelligent, image-based asset management, creating a digital inventory of their transmission and distribution networks. This enables improved asset data quality, safer operations, reduced inspection costs, and extended asset life. With more than 20 years of international experience, eSmart Systems supports utilities worldwide in building smarter, more resilient grids for the future.

Featuring:

• Josh Allison, SVP Commercial, eSmart Systems
• Don McPhail, VP Market Development, eSmart Systems

In a recent address to federal regulators, North American Electric Reliability Corp (NERC) President and CEO Jim Robb described today’s grid reliability challenge as a “five-alarm fire.” He warned that while the reliability of the U.S. grid remains high, the risks to that reliability are intensifying because of extreme weather, growing demand, and aging infrastructure.

Among those risks, few are as destructive or costly as wildfires caused by electrical equipment failures.
In this discussion, Don McPhail and Josh Allison reflect on NERC’s warning and explore how AI-powered tools like Grid Vision® are helping reduce grid-related wildfire risk through proactive, data-driven insights.

Don: Josh, the NERC President called the state of grid reliability a “five-alarm fire.” When you look at recent wildfire events and infrastructure-related ignitions, that metaphor feels literal. What are you seeing from utilities right now? 

Josh: You’re spot on, Don. Utilities are living that reality. Drought, heat, and aging infrastructure have created a perfect storm. Many U.S. states, especially in the West, are facing unprecedented wildfire seasons. What we’re hearing is that utilities want to move from reactive inspection programs to predictive maintenance because every undetected defect or vegetation strike is a potential ignition. 

Don: The article mentioned “small-scale events and near misses” increasing. How does that tie into wildfire risk? 

Josh: Those “near misses” are exactly what we’re helping utilities identify earlier. A cracked insulator, a corroded clamp, or a frayed conductor might not cause an outage today, but in dry, windy conditions it can become an ignition point tomorrow. Grid Vision’s AI scans through vast image data to find those early indicators before they escalate, allowing maintenance teams to act on real risk instead of probability. 

Don: The NERC discussion also raised the need for better “shock absorbers” in the system, meaning tools that help utilities manage uncertainty. What does that look like in the context of wildfire prevention? 

Josh: Wildfire risk changes constantly with temperature, vegetation growth, and asset condition. AI becomes that “shock absorber” by continuously analysing new imagery and risk data. With Grid Vision, utilities can see which areas are trending toward higher ignition risk and proactively allocate inspection and repair crews before the fire season peaks. 

Don: The article also raised concerns around cost and affordability, that improving resilience can be expensive. How do utilities balance that with the pressure to reduce wildfire risk? 

Josh: Prevention is always cheaper than recovery. Through AI automation, we’re helping utilities cut inspection costs by more than 50 percent while covering more assets in less time. That efficiency allows them to expand wildfire mitigation programs without increasing operational costs, which is a win for both regulators and customers. 

Don: So, responding to NERC’s “five-alarm fire” is not only about building more infrastructure. It is also about understanding and managing what already exists more effectively. 

Josh: Exactly. Reliability starts with visibility. The grid is changing faster than anyone can rebuild it, but AI gives utilities the ability to monitor, predict, and prevent. That is how we put out the fire before it starts. 

The NERC warning highlights one clear truth: reactive maintenance is no longer enough. 

Featuring:

• Don McPhail, VP Market Development, eSmart Systems
• Erik Åsberg, Chief Technology Officer, eSmart Systems

In today’s energy landscape, utilities are under pressure to do more with less, modernize aging infrastructure, respond to extreme weather, and meet rising expectations for reliability and sustainability. At the center of this transformation is data. But data alone isn’t enough. It’s what you do with it that matters. Join us as we go behind the scenes of eSmart Systems’ Grid Vision^® platform to explore how our intelligence layer is helping utilities turn raw inspection data into real-time decisions with AI, digital twins, and a smarter approach to grid management.

Don McPhail:
I’m joined today by Erik Åsberg, our Chief Technology Officer here at eSmart Systems. Erik has been leading the development of our AI and data platform strategy for over a decade and is widely recognized as a thought leader in applying advanced technologies to utility operations.
Erik, we often talk about Grid Vision^® as a game-changer for utilities. But behind the scenes, there’s a powerful data platform making it all possible. Can you walk us through what that platform actually does?

Erik Åsberg:
Absolutely. At the heart of Grid Vision^® is our intelligence platform, a cloud-native system that ingests, organizes, and analyzes all inspection data. Whether it’s drone imagery, infrared scans, LiDAR, or even handwritten field notes, the platform links everything to the utility’s assets. The result is a living digital twin of the grid.
But it’s not just about storing data. The platform transforms raw inspection inputs into structured, actionable intelligence. It gives utilities a single source of truth for asset condition, enabling them to shift from reactive maintenance to proactive, risk-based decision-making.

Don:
So it’s not just a database, it’s a decision engine?

Erik:
Exactly. Utilities have no shortage of data. The challenge is making sense of it. What makes our intelligence platform unique is that it brings together three key dimensions:

• A graph-based model that reflects how assets are physically and electrically connected, so every pole, conductor, and substation is contextually linked.
• Time-series history, which tracks how asset conditions evolve over time, enabling trend analysis and predictive maintenance.
• Spatial awareness, integrating GIS and environmental data to understand where assets are located and what risks they face, like terrain, vegetation, or weather exposure.

Together, these dimensions create a rich, intelligent model of the grid. This structure allows for fast, intelligent queries, like identifying aging assets with recurring defects, and enables seamless integration with AI, so insights can be surfaced and acted on in real time.

Don:
Let’s talk about that AI. How does the platform support the AI capabilities in Grid Vision^®?

Erik:
It’s AI-ready by design. Because the data is structured and fully connected, it’s ideal for training and deploying machine learning models. For example, our AI can detect defects in images and automatically associate those findings with the correct pole or component.
We’ve also integrated natural language interfaces. You can literally ask the system, “Show me all critical defects within 5 miles of a substation,” and it will return results instantly. That’s the power of combining structured data with modern AI.

Don:
That’s incredibly powerful. What about integration with other utility systems, GIS, EAM, BI tools?

Erik:
We’ve made openness a core principle. The platform exposes standard APIs and supports a query language familiar to many data teams. That means utilities can pull data into their existing systems without vendor lock-in.
And because we support spatial, temporal, and graph-based data, it’s easy to add new sources, like weather feeds or new sensor types, without rearchitecting anything.

Don:
Utilities are dealing with massive volumes of data. How does the platform support scale?

Erik:
Great question! It’s built on modern cloud infrastructure and designed to handle the scale and complexity of utility operations. Whether you’re managing 10,000 assets or 10 million, the platform can ingest, organize, and analyze that data in real time. As an example, we’re working with many large utilities across North America and Europe such as Evergy, Xcel Energy and E.ON.
And it’s secure, as demonstrated via our ISO 27001 compliance, and support of technologies such as SSO and multifactor authentication. Utilities retain full ownership of their data, including hosting data in their local region, and we provide enterprise-grade access controls to ensure privacy and compliance.

Don:
One thing I hear often is the need for faster insight-to-action cycles. How does the platform help with that?

Erik:
That’s one of its biggest strengths. Traditional inspection workflows are slow and fragmented. With our platform, everything is connected and instantly quarriable. You can go from image capture to defect detection to maintenance planning in hours, not weeks.
And because we support predictive analytics, utilities can start to anticipate failures before they happen. That’s the future: a grid that’s not just monitored, but truly intelligent.

Don:
Final question, what excites you most about where our technology and intelligence platform are headed?

Erik:
It’s the convergence of AI, digital twins, and real-time data. We’re building more than a platform, we’re building a foundation for autonomous grid operations. As we integrate more AI capabilities and natural language tools, we’re making it easier for utilities to interact with their data and act on it. This is only increasing in importance as we seek to make the grid more efficient and adaptable to extreme weather, changing supply side, and growth in demand.
We’re not just helping utilities inspect assets, we’re helping them reimagine how the grid is managed, making them more efficient in having AI take on the mundane and tedious work, and prioritize their investments where it’s needed most.

Don:
Thanks, Erik. For utilities navigating aging infrastructure, climate risk, and rising expectations, this platform offers something rare: clarity, speed, and control. That’s what real transformation looks like.

Want to learn more about how Grid Vision^® and our intelligence platform can help your utility? Book a demonstration or reach out to our team to see how we’re helping utilities turn data into decisions.

August 2025 – Wildfires are becoming an increasingly severe global challenge, with rising temperatures, prolonged droughts, and climate change creating perfect conditions for disasters. The devastation caused by wildfires is evident worldwide: the 2019–2020 Australia Bushfires (Black Summer), the 2023 Greece wildfires in Rhodes, Canada’s 169 reported wildfires by July 2023, Turkey’s 19 wildfires since mid-July 2023, and France’s massive fire burning over 2,500 acres along the Mediterranean coast. More recently, the 2025 Los Angeles wildfire underscored the growing risks.

While wildfires have natural and human-related causes, power grids have also emerged as a significant ignition source. Grid-related wildfires can occur due to falling trees, vegetation contact, aging components, or sparks from failing infrastructure. As utilities face increasing regulatory scrutiny and public pressure to mitigate these risks, artificial intelligence (AI) and advanced data solutions are proving to be transformative.

The growing role of AI in wildfire mitigation

Last week, a new executive order from President Trump called for agencies to create a roadmap leveraging AI, data sharing, modeling, and mapping capabilities to identify wildland fire ignitions and improve weather forecasting for better emergency response. A federal fund of $3.8 billion, although mostly a reallocation of existing resources, underscores the urgency for advanced wildfire management.

This directive aligns with the growing role of technology in wildfire prevention, including AI-based grid inspections and image data that leverage vegetation management and condition-based insights to ensure the physical grid is safe and in good working order. These insights help minimize fire risk.

Federal efforts, such as the recent $3.8 billion wildfire management fund and the executive order calling for AI-driven modeling and data sharing, could make this type of image and condition data more accessible to utilities and research initiatives. By promoting standardized data-sharing frameworks, subsidizing advanced imaging technology, and supporting AI training programs, these efforts enhance AI models by giving them larger, higher-quality datasets for defect detection and risk prediction, ultimately improving accuracy and reliability.

For utilities, this policy shift emphasizes the need to go beyond traditional inspections, leveraging AI platforms like Grid Vision^® to detect early-stage defects and proactively mitigate wildfire hazards.

Why grid-related wildfires are rising

Power grids are under stress due to climate-driven heat waves, severe droughts, and increased vegetation growth. Aging infrastructure often fails to keep up with these conditions. Factors contributing to grid-related wildfires include: 

• Tree or branch contact with powerlines. 
• Exploding material or sparks from faulty components. 
• Arcing or conductor failures due to loose hardware. 
• Dry vegetation surrounding powerlines acting as fuel. 

Conductors play a key role in preventing fire hazards. To ensure safety: 

• Vegetation must be cleared around lines. 
• Conductors must remain separated using spacers. 
• Cotter pins and related hardware must remain securely fixed. 
• C-hooks and chain shackles must be inspected for wear, corrosion, or deformation. 

Loose or upside-down cotter pins and worn or damaged C-hooks compromise the safety barrier by weakening the points where conductors and insulators are secured. This increases the risk of conductors falling or generating sparks when in contact with nearby surfaces. A single cotter pin failure on a 100-foot lattice tower can have devastating consequences, and a worn C-hook can create stress points that accelerate component failure under wind or load. Yet manually inspecting 50 cotter pins and multiple C-hooks per tower is both tedious and prone to human error. 

AI-supported virtual inspections are a game-changer

The 2025 Los Angeles wildfire and the 2018 Camp Fire in Butte County, and the 2025 Eaton wildfire in Los Angeles highlight the devastating consequences of delayed or insufficient grid inspections. The Camp Fire remains the deadliest and most destructive wildfire in California’s history, underscoring why utilities must move beyond slow, manual inspection cycles.

Southern California likely has 3,500 to 4,000 lattice-steel transmission towers. Manual climbing inspections take about 2 hours per tower, meaning a single inspector would need 3.5 to 4 years to complete one full cycle. In contrast, drone-assisted inspections reduce that timeline to 7 months to 1.5 years, resulting in an efficiency gain of up to 80%.

AI-powered image analysis further accelerates the process by detecting and classifying defects within seconds, removing the need for hours of manual image review and enabling fast, data-driven maintenance decisions.

Solutions like Grid Vision® create a digital representation of the grid by linking high-resolution imagery, asset metadata, and grid topology into one platform.

Key benefits include:

• Faster defect detection and automated workflows
• Lower inspection costs and reduced manual efforts
• Safer operations by minimizing tower climbs
• Regulatory-ready, auditable visual data
• Early detection of high-risk defects, such as corrosion or faulty hardware

Case study: AI-supported inspections and advanced analytics for wildfire risk management

A leading North American utility leveraged AI-powered inspections to strengthen its wildfire prevention strategy. Using drone flights combined with AI analytics, the utility inspected 47 lattice towers and 52 wooden poles, capturing 3,465 high-resolution images in total.

AI findings:

• 781 instances of upside-down cotter pins were detected out of 11,000 cotter pin images, within seconds.
• Loose cotter pins, chain shackles, and contaminated insulators were flagged for immediate maintenance.
• Additional anomalies such as woodpecker holes, flashed insulators, and cracked poles were identified.

Project outcomes:

• The customer confirmed their grid’s good condition regarding C-hooks and shackles.
• Maintenance teams could target defect repairs without climbing towers, improving safety.
• AI’s speed and accuracy allowed the customer to proactively correct wildfire-relevant defects, preventing potential ignition events.

Vegetation management and conditional data

Vegetation is a primary fuel source for grid-related fires. AI-powered platforms use high-resolution imagery combined with conditional data from inspections to monitor vegetation encroachment and assess the overall health of grid assets.

Grid Vision® includes a “Vegetation Right of Way” filter that allows utilities to:

• Identify assets in densely vegetated areas.
• Pre-plan field work, reducing time and site visits.
• Assess site access needs before sending maintenance crews.

By combining vegetation data with condition-based insights, utilities can create a more accurate view of wildfire risks and take proactive measures to mitigate them.

Beyond inspections: predictive insights

AI-driven platforms offer more than just defect detection. With historical data and year-over-year comparisons, utilities can identify patterns that may increase wildfire risk, such as:

• Wooden poles rotting near water due to humidity.
• Asset degradation based on age or material type.
• Recurring vulnerabilities across similar asset classes.

The holistic asset data in Grid Vision® enables utilities to overlay additional datasets, such as roads, gas pipelines, or water bodies, onto their grid map. This contextual data supports better planning, risk prioritization, and faster incident response.

Common vulnerabilities and incident investigations

When a failure occurs, such as an MV substation outage, traditional utilities may lack recent, high-quality imagery to reconstruct the cause.

With AI-powered inspections, utilities gain:

• Accurate, structured visual data of substations and transmission lines.
• A full audit trail for regulatory reporting.
• The ability to conduct root cause analysis and prevent future incidents.

For example, one utility used inspection data to locate and replace a lightning arrestor flagged by regulators as a fire hazard. Without the AI-driven inventory, they would not have known where these components were installed.

Federal and industry momentum

The $3.8 billion federal initiative and policy emphasis on AI highlight the government’s recognition that data-driven approaches are critical to wildfire mitigation. This is not just a challenge for California but a national and global issue.

As utilities seek to modernize operations, partnerships between AI inspection providers, satellite imaging companies, and wildfire modeling solutions will play a critical role. Platforms like Grid Vision® can provide ignition source risk data, feeding into larger wildfire prevention ecosystems.

Key steps utilities can take now

In summary

Wildfires are no longer an isolated risk, they are a global crisis intensified by climate change and aging grid infrastructure. AI-powered tools like Grid Vision® give utilities the ability to detect 60 percent more defects than traditional inspections, reduce operational costs, and most importantly, prevent fire ignitions before they happen.

From cotter pin detection to vegetation monitoring, virtual inspections create a digital twin of the grid, enabling utilities to compare asset conditions over time, plan maintenance more effectively, and improve safety for both workers and communities.

The message is clear: AI and data-driven insights are the future of wildfire prevention. With federal funding and policy momentum supporting innovation, now is the time for utilities to embrace technology that will save time, reduce costs, and protect lives and infrastructure from catastrophic fires.

September 2025 – In a world where energy infrastructure must be smarter, faster, and more resilient, eSmart Systems and Equinor are leading a pioneering researching collaboration: the Infrastructure for Faster, more Accurate Analytics (IFAA) project.

Born from eSmart Systems’ deep roots in artificial intelligence and formally approved by the Research Council of Norway, IFAA is more than a research initiative. It is a step into the future of infrastructure inspection and defect detection. The project has already delivered transformative innovations, including Adaptive AI, a patent-pending technology that drastically reduces retraining time for AI models and enables real-time tuning based on user feedback.

Recognizing the project’s potential to establish a new benchmark for how utilities harness AI, eSmart Systems identified an opportunity to push the limits of model training and automation in real-world conditions. By developing smarter, adaptive systems that can continuously learn from data and feedback, the project aims to help energy companies achieve faster insight generation, greater operational accuracy, and more proactive maintenance strategies. Equinor joined as a strategic partner, bringing decades of operational expertise and a shared vision for AI-driven transformation. Together, the teams are exploring the frontiers of computer vision and applying innovations such as AI that learns from fewer examples, creating step-change improvements in efficiency and accuracy.

At the heart of IFAA is a commitment to open innovation. While each partner retains their intellectual property, learnings are shared across sprints, creating a dynamic feedback loop that accelerates progress and deepens insight. Both companies noting advancements in defect detection and AI-driven inspection automation. The collaboration now looks ahead to further expanding its impact by exploring varied use cases within each organization to drive even greater operational value.

Together, eSmart Systems and Equinor are turning AI into practical solutions that deliver value today while aiming to drive a smarter, safer, and more resilient energy sector for the future.

About Equinor

Equinor is an international energy company committed to long-term value creation in a low-carbon future. The company is headquartered in Norway with around 25,000 employees and with offices in more than 20 countries.

About eSmart Systems

eSmart Systems is a global leader in AI-powered solutions for the inspection, analysis, and digitalization of critical grid infrastructure. Through our Grid Vision® platform, we help utilities transition from manual inspections to intelligent, image-based asset management, creating a digital inventory of their transmission and distribution networks. This enables improved asset data quality, safer operations, reduced inspection costs, and extended asset life. With more than 20 years of international experience, eSmart Systems supports utilities worldwide in building smarter, more resilient grids for the future.

August 2025 – Evergy, a leading U.S. utility serving 1.7 million customers across Kansas and Missouri, has renewed its commitment to digital asset management through an extended collaboration with eSmart Systems. Building on the success of a 3.5-year digitalization and inspection program powered by Grid Vision^®, Evergy will continue to expand its digital asset strategy to create a future-ready, data-driven grid.

The original program transformed over 10,100 miles of Evergy’s transmission network into a centralized, visual asset repository, creating a full digital inventory of every transmission asset down to the component level. Over 1 million high-resolution images were linked to asset records, while 70,000+ annotated defects were cataloged to prioritize maintenance and repairs. This complete and searchable asset inventory has enabled engineering, real estate, and operations teams to access reliable, up-to-date data, dramatically improving data accuracy and situational awareness.

With this renewal, Evergy will continue to assess transmission inspections while expanding the use of Grid Vision^® to its distribution grid and digitalizing new asset types, including the full digitalization of inspections and imagery for underground vaults. By consolidating these asset types into a unified platform, Evergy will gain a deeper understanding of asset health across its entire network, enabling more accurate risk-based analysis and investment decisions.

Through this renewal, Evergy and eSmart Systems will continue working together to advance virtual inspections, enhance safety by minimizing unnecessary fieldwork, and support the transition toward a modernized, fully digital grid.

The continued collaboration will enable Evergy to expand its digital asset inventory, streamline inspection workflows, and unlock deeper insights to support the growing demands of a modern utility grid.

About Evergy

Evergy (NASDAQ: EVRG) provides electricity to 1.7 million customers across Kansas and Missouri. Headquartered in Kansas City, Evergy is a vertically integrated utility committed to delivering safe, reliable, and affordable energy. The company is actively investing in grid modernization and sustainable infrastructure to support a resilient, future-ready energy system. For more information, visit https://www.evergy.com/

About eSmart Systems

eSmart Systems is a global leader in AI-powered solutions for the inspection, analysis, and digitalization of critical grid infrastructure. Through our Grid Vision® platform, we help utilities transition from manual inspections to intelligent, image-based asset management, creating a digital inventory of their transmission and distribution networks. This enables improved asset data quality, safer operations, reduced inspection costs, and extended asset life. With more than 20 years of international experience, eSmart Systems supports utilities worldwide in building smarter, more resilient grids for the future.

12 August 2025 – eSmart Systems’ Grid Vision^® has been named a winner in the Best SaaS Solution for Energy, Utilities or Telecoms at The 2025 SaaS Awards.

Operated by global cloud computing awards body The Cloud Awards, The SaaS Awards judges have completed their final round of assessment of the finalists, resulting in winners being selected in each category.

The SaaS Awards celebrates outstanding levels of innovation and excellence in the software-as-a-service industry, from business process improvement solutions to cutting-edge uses of AI, and both niche and generalized services. The program received entries from organizations of all sizes across the globe, including the USA and Canada, the UK and Europe, the Middle East, and APAC.

The program will return to welcome new submissions in 2026, continuing to recognize the latest advancements in software-as-a-service.

To view the full list of winners, visit The Cloud Awards website.

Entries are now open for the long-running Cloud Awards program, which recognizes organizations at the forefront of cloud computing. Submissions are open until October 24, with earlybird entries accepted until August 29. Entries to other Cloud Awards programs, including The FinTech Awards and The Security Awards, both concluding in 2026, are also open.

About The Cloud Awards

The Cloud Awards is an international program which has been recognizing and honoring industry leaders, innovators and organizational transformation in cloud computing since 2011. The Cloud Awards comprises five awards programs, each uniquely celebrating success across cloud computing, software-as-a-service (SaaS), cloud security, artificial intelligence (AI), and financial technologies (FinTech).

Winners are selected by a judging panel of international industry experts.

About The Cloud Awards Program

The Cloud Awards identifies and celebrates the most innovative organizations, technologies, individuals and teams in the world of cloud computing. The program spans 36 categories, including ‘Best Cloud Infrastructure’ and ‘Best Cloud Automation Solution’. 

About The SaaS Awards    

The SaaS Awards focuses on software-as-a-service, with categories segmented into overall SaaS excellence, by sector, business operational processes, or outstanding uses of certain technologies (such as AI).

About eSmart Systems

eSmart Systems is a global leader in AI-powered solutions for the inspection, analysis, and digitalization of critical grid infrastructure. Through our Grid Vision^® platform, we help utilities transition from manual inspections to intelligent, image-based asset management, creating a digital inventory of their transmission and distribution networks. This enables improved asset data quality, safer operations, reduced inspection costs, and extended asset life. With more than 20 years of international experience, eSmart Systems supports utilities worldwide in building smarter, more resilient grids for the future.

With global electricity demand projected to grow by 4% in both 2024 and 2025*— one of the fastest growth rates seen in two decades — utilities face the pressing challenge of ensuring their grids can meet this surge reliably and sustainably.

Rising energy consumption and the integration of renewable energy sources make it essential not only to add capacity but to do so smartly and sustainably. We have seen first-hand there is one crucial element to meet this effectively: accurate grid asset data.  

Without this, utilities are essentially navigating blind. By understanding the true state of the grid’s condition, utilities can not only handle current loads but also plan smartly for future expansions and repairs. 

At the heart of effective grid management is accurate asset data. 

For utilities, maintaining a complete and up-to-date picture of their infrastructure is essential. Without it, effective operations management, future planning, and smart investment decisions become nearly impossible.  The first step toward improving the accuracy of grid asset data can begin with activities like grid inspections or a data quality improvement activities like grid inventory programs.

For either of these activities, utilities need to ensure that the data collection is focused on image-based asset data, collected with high-resolution cameras that capture detailed views of the infrastructure. These images, when processed through advanced tools like Grid Vision^®, provide a visual inventory of assets, cataloging them with pinpoint accuracy and linking the asset to additional information like inspection data. 

What benefits can you achieve with image-based accurate asset data? 

Once utilities start collecting and leveraging accurate image-based data, they can unlock several critical benefits that support operational efficiency and long-term grid resilience: 

1. Efficient Maintenance: Precise image-based data enables condition-based maintenance. This allows utilities to identify assets that require attention before they fail. This proactive strategy reduces outages, extends asset life, and prevents costly emergency repairs​. 
2. Better Investment Decisions: Accurate, consistent and objective insights of grid infrastructure condition allows utilities to prioritize capital investments based on risk. For example, virtual inspections enabled by AI can highlight critical areas where repairs are needed, helping to allocate resources where they will have the most impact​. 
3. Enhanced Planning for Growth: Accurate image-based asset data supports improved  forecasting for future grid expansion or reinforcement. As demand rises, utilities must not only repair existing infrastructure but also build new assets.  
4. Improved Safety and Compliance: Knowing the exact status of grid components ensures compliance and reduces the risk of incidents. This compliance aspect is particularly important as aging infrastructure and increased renewable energy integration strain the grid​. 

Data as the Cornerstone of Grid Management 

Accurate, reliable asset data is more than a convenience—it’s essential to managing current operations effectively and preparing for sustainable growth.  

By embracing advanced digital tools, like Grid Vision, and leveraging the power of AI, utilities can transform their data collection and asset management practices, ensuring they stay ahead of the curve in a rapidly evolving energy landscape​. 

*Source: International Energy Agency (IEA) report, 2024 forecasts on electricity demand growth. 

Want to see a demo of Grid Vision? Fill this form here  

eSmart Systems, a global leader in AI-based solutions for inspection and maintenance of critical energy infrastructure, has successfully raised EUR 30 million in new capital. The funding round has been led by TiLT Capital, the French energy transition platform of the Siparex Group, and with Quanta Services participating as a strategic investor.

Oslo, Norway, October, 2024 – eSmart Systems announces that it has raised EUR 30 million. TiLT Capital Partners, a French growth capital impact fund led the round, with major US energy infrastructure solutions company Quanta Services, Inc. (Quanta), joining as a strategic investor. Additionally, major existing owners Arosa Capital, Energy Impact Partners, Equinor Ventures, Nysnø Climate Investments, Future Energy Ventures and Kongsberg Group have participated in the capital raise.

The capital raise comes at a time of very strong demand for eSmart Systems, which has recently signed several strategic contracts with prominent customers such as Alliander and E.ON. With a total of EUR 63 million raised over the past two years, eSmart Systems not only reaffirms strong investor interest but also solidifies its position as one of the best-funded companies in the industry. This financial strength positions eSmart Systems uniquely to capture significant market opportunities and drive innovation in AI-based solutions for critical energy infrastructure.

Strong market uptick

A global pioneer in AI-based solutions for inspection and digitalization of critical energy infrastructure, eSmart Systems operates in a market that is currently experiencing a strong uptick due to a combination of factors.

Electric utilities face significant challenges with a global grid at the risk of collapse due to aging infrastructure, increased energy consumption and more frequent extreme weather events. Lack of quality asset data compromises their ability to efficiently manage the grid.

Growth driver in North America

With Quanta joining eSmart Systems as a strategic investor, the two companies plan to collaborate on virtual inspection and grid digitalization services in the North American market, leveraging Quanta’s extensive scale, resources and expertise and eSmart Systems’ cutting edge digital solutions.

“We are very excited to bring Quanta onboard as an investor and a strategic partner. Our joint capabilities will be unmatched in the market, making us uniquely equipped to help transition utilities to more data driven and proactive operations.”, says Bache.

About eSmart Systems

eSmart Systems is a leading provider of AI-powered solutions for the inspection and maintenance of critical infrastructure. With the Grid Vision® portfolio, the company provides Inspection Management and Asset Information Management solutions and services to utilities globally. Grid Vision provides a data-driven and condition-based approach to infrastructure inspections and support utilities to reduce inspection costs, improve inspection safety, improve the quality of asset data and prolong asset life. More information about the company can be found at www.esmartsystems.com.

About TiLT Capital Partners

Created in 2018, TiLT Capital joined Siparex – an independent French specialist in Private Equity – in 2021 to become the Energy Transition platform of the Group. This collaboration has created a unique platform, combining the experience of a major player in Private Equity with the expertise of a team with over 50 years of experience in the energy industry, to meet the growing financing needs of the Energy Transition. More information about the company can be found at https://www.tilt-capital.com/en/

About Quanta Services, Inc.

Quanta is an industry leader in providing specialized infrastructure solutions to the utility, renewable energy, technology, communications, industrials, and pipeline industries. Quanta’s comprehensive services include designing, installing, repairing and maintaining energy and communications infrastructure. With operations throughout the United States, Canada, Australia and select other international markets, Quanta has the manpower, resources and expertise to safely complete projects that are local, regional, national or international in scope. For more information, visit https://www.quantaservices.com

Our new investors are joining Arosa Capital Management, Energy Impact Partners, Equinor, Future Energy Ventures, Kongsberg and Nysnø Climate Investments and together we will continue to support the energy transition through Grid Vision.