Audience

Communities looking for a wildfire detection and intelligence solution to quickly mitigate wildfire threats

About Pano

The early minutes of a fire are critical, and initial response time determines the ultimate threat to lives and property. With most wildfires detected by bystanders and reported via 911, it can take hours to detect a fire, verify its exact location and size, and dispatch first responders. Pano Rapid Detect speeds response time by empowering detection specialists with enhanced visual equipment and rapid data analysis, supported by AI. Specialists have a single, unified view combining ultra-high-definition cameras, geo satellite data, field sensors, legacy cameras, emergency alerts, and other data feeds — as well as the ability to share everything in real-time with their extended team. Altogether, this makes it possible to quickly identify and contain devastating wildfires, protecting lives, property, and our forests.

Integrations

No integrations listed.

Ratings/Reviews

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Company Information

Pano
Founded: 2019
United States
www.pano.ai/

Videos and Screen Captures

Pano Screenshot 1
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Product Details

Platforms Supported
Cloud
Training
Live Online
Support
Online

Pano Frequently Asked Questions

Q: What kinds of users and organization types does Pano work with?
Pano works with these users and organization types: Mid Size Business, Small Business, Enterprise, Freelance, Nonprofit, Government, and Startup.
Q: What languages does Pano support in their product?
Pano supports these languages: English.
Q: What kind of support options does Pano offer?
Pano offers support via online.
Q: What type of training does Pano provide?
Pano provides training in the form of live online.

Pano Product Features

Fire Department

Custom Map Views Not Supported
Search Not Supported
Equipment Tracking Not Supported
Event Calendar Not Supported
Scheduling Not Supported
In-Vehicle Navigation Not Supported
Pictometry Imagery Not Supported
Facility Pre-planning Data Not Supported
Incident Response Checklists Not Supported