As wildfires become more frequent and destructive, the need for rapid detection and response has never been more urgent. In 2024 alone, nearly one billion acres burned worldwide, highlighting the scale of the crisis and the limitations of traditional firefighting approaches.
Against this backdrop, Pano AI—a San Francisco-based startup—has raised $44 million in Series B funding to expand its AI-powered wildfire detection infrastructure, signaling a broader shift in how technology and insurance sectors are investing to reduce wildfire risks.
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What does Pano AI do?
Pano AI develops and deploys an integrated platform for early wildfire detection and situational awareness, targeting fire agencies, utilities, governments, and private landholders. At the heart of its solution is a network of ultra-high-definition, 360-degree cameras installed on high vantage points across fire-prone landscapes. These cameras, combined with proprietary AI models, continuously scan for smoke and other fire indicators, day and night, across nearly 30 million acres in the U.S., Canada, and Australia.
The system operates as follows:
- Continuous Monitoring: Cameras capture panoramic images every minute and relay them to the cloud for AI analysis.
- AI-Powered Detection: Advanced computer vision algorithms detect early signs of smoke or fire, flagging potential incidents in real-time.
- Human Verification: A team of analysts at the Pano Intelligence Center reviews AI-flagged events to minimize false positives.
- Rapid Notification: Once verified, alerts with precise GPS coordinates are sent to first responders and partners via SMS or email, enabling faster, more targeted responses.
- Integrated Data Feeds: The platform incorporates satellite imagery, weather data, and third-party GIS sources to enhance situational awareness for emergency managers.
Pano AI’s technology has already been credited with enabling rapid responses to emerging fires. For instance, during the Bear Creek Fire in Colorado, Pano AI detected smoke within minutes, allowing emergency teams to contain the fire to just three acres—a crucial intervention for a watershed serving over a million people.
Founding inspiration and mission: Insights from Sonia Kastner
Pano AI was founded in 2020 by Sonia Kastner and Arvind Satyam, both of whom have deep roots in the tech sector. Sonia previously worked at Nest, where she contributed to the development of one of the first AI-enabled smart cameras, while Arvind spent years at Cisco helping build smart cities like Barcelona and Copenhagen.
The inspiration for Pano AI came after they saw an executive order from the State of California calling for “innovative ideas” to support wildfire mitigation. They were surprised by the lack of real-time visibility available to first responders—no shared maps, no common operating picture, and no situational awareness. “It didn’t feel like an intractable problem. It felt like something we knew how to solve,” Sonia explained.
This realization became the foundation for Pano AI. The company’s mission has remained consistent: “to get the best possible technology into the hands of first responders and emergency managers on the front lines of the wildfire crisis”.
How are they unique and who are the competitors?
Pano AI distinguishes itself through a combination of advanced hardware, proprietary AI, and a full-stack, managed service model. Unlike some competitors that focus solely on satellite data or ground sensors, Pano integrates high-resolution camera feeds, AI analysis, and human verification into a single, turnkey platform. This holistic approach is designed to reduce both false positives and detection latency, two major challenges in wildfire management.
The company’s patented triangulation technology provides highly accurate incident locations, while its cloud-based platform allows for real-time collaboration among agencies and utilities. Pano also emphasizes community engagement, offering training and workshops to ensure that local responders can make full use of the system’s capabilities.
Competitive landscape
The wildfire detection sector has grown rapidly, with several notable players:
Dryad Networks: Specializes in solar-powered, mesh-networked gas sensors for ultra-early detection, particularly in remote forests. Their system is scalable and sustainable, but relies on ground-based sensors rather than panoramic imagery.
Robotics Cats: Focuses on AI-driven machine vision and IoT solutions, often partnering with drone and satellite providers for multi-layered wildfire management.
ALERTCalifornia: A public safety program leveraging a vast network of cameras and AI to provide early detection and real-time data to first responders, especially in California.
Fireball.International: Uses deep learning and satellite data to detect and track wildfires globally, providing real-time intelligence for rapid response.
Wildfire Defense Systems: Offers risk management and loss intervention services, focusing on pre- and post-fire mitigation for insurers.
While Pano AI is not the first to use cameras and AI for wildfire detection, it has emerged as a leader in integrating these technologies at scale and providing a managed service to both public and private sector clients. Its client base includes over 250 first responder agencies and 15 major utilities, such as Arizona Public Service, Portland General Electric, and Xcel Energy.
Valuation, funding, and team: Growth and background
Pano AI’s $44 million Series B round, led by Giant Ventures and joined by Liberty Mutual Strategic Ventures, Tokio Marine Future Fund, and others, brings its total funding to $89 million. The company’s contracted revenue now exceeds $100 million after four years of rapid growth, supporting coverage of nearly 30 million acres worldwide.
While the precise post-money valuation was not disclosed, the scale of funding and revenue growth positions Pano AI as one of the most well-capitalized startups in the wildfire tech space.
Team size and composition
Today, Pano AI has 110 team members across North America and Australia. This multidisciplinary team includes experts in AI, engineering, operations, emergency management, and public policy—reflecting the complexity and urgency of the wildfire problem. Sonia Kastner notes, “Solving this problem requires both technological depth and an understanding of how decisions get made on the front lines.”
The broader team includes professionals from companies like Cisco, Tesla, Apple, Salesforce, and Nest, reflecting a blend of tech and climate expertise.
What’s next: Scaling up and global ambitions
With the Series B funding, Pano AI is focused on accelerating deployment in high-risk areas and expanding access to real-time wildfire intelligence. The immediate priority is to grow its footprint in the U.S., Australia, and Canada as high-risk zones emerge and evolve. At the same time, the company is investing in further AI capabilities, expanding sensor inputs, and deepening integration with technology partners to help emergency managers act faster and with greater confidence.
Sonia Kastner emphasizes that the company’s mission is not just about technology, but about building resilience: “This additional capital allows us to accelerate our mission to equip first responders with the best technology to protect communities, safeguard our critical infrastructure, and build a more resilient future”.
What do we think about Pano AI in the larger picture?
The emergence of Pano AI reflects a broader trend: the fusion of AI, IoT, and cloud computing to address climate-driven disasters. As wildfires increase in both frequency and severity due to climate change, early detection and rapid response are becoming essential components of resilience strategies for communities, utilities, and insurers.
Pano AI’s approach—combining high-definition imagery, AI, and human verification—addresses some of the main shortcomings of earlier systems, such as high false positive rates and limited coverage. Its managed service model also lowers the barrier to adoption for agencies that may lack in-house technical capacity.
However, the effectiveness of AI-driven wildfire detection is still being evaluated in real-world conditions, especially as climate patterns shift and fire behavior becomes more unpredictable. Programs like ALERTCalifornia and competitors such as Dryad and Robotics Cats are also pushing the boundaries of what’s possible, using a mix of sensors, satellite data, and AI to complement or compete with Pano’s approach.
The sector is likely to see further innovation and consolidation as governments, utilities, and insurers seek reliable, scalable solutions. The inclusion of Pano AI in MIT Technology Review’s “15 Climate Tech Companies to Watch” list underscores the growing recognition of climate adaptation technologies in the broader tech ecosystem.
What we think about the startup
Pano AI’s $44 million Series B funding round marks a significant milestone in the evolution of wildfire detection technology. By integrating AI, high-definition cameras, and real-time data feeds, Pano AI aims to provide first responders and infrastructure operators with the tools needed for faster, more informed decision-making. The company’s rapid growth, expanding customer base, and strong investor backing reflect both the urgency of the wildfire crisis and the promise of technology-driven solutions.
Yet, as the wildfire threat intensifies and new competitors emerge, the effectiveness and scalability of these solutions will be tested on the front lines. The coming years will reveal whether Pano AI and its peers can deliver on the promise of early detection and help communities adapt to a world where wildfires are an ever-present risk
