Case Study

Avista improves the customer experience with AI-powered weather and incident forecasting



Netze BW realizes high accuracy with satellite and AI vegetation assessments

A climate risk intelligence system enables a utility to proactively prepare for storms 


  • Company: Avista Utilities
  • Location: United States
  • Solution: Climate Risk Intelligence System (CRIS)


Better understanding of impact on service territory, starting 72 hours in advance

Decreased estimated restoration time (ERT)

Greater than 80% accuracy in storm impact predictions in the pilot



Avista wanted to be able to respond faster to severe weather events and communicate better with customers about those events. 

In November of 2023, Avista had the worst gas outage in their history. Because of a dig-in, 36,000 customers were without natural gas. Avista sent all of their resources, comprising some 400 personnel and more than 800 mutual aid assistants.

Then, a storm hit, confounding the situation. Avista had to quickly redirect a sizable portion of their resources to go and restore power in their Spokane, Washington, service area.

But Avista had AiDash Climate Risk Intelligence System (CRIS), which alerted them to an oncoming storm before it landed. 

Avista provides electricity to 406,000 customers and natural gas to about 372,000 customers across 30,000 square miles. The service area extends across all or part of Washington, Oregon, Idaho, and Montana.

Avista did more than 500 interviews with customers, account executives, and other internal resources to get better information about how they could improve their storm responses. The feedback they got indicated they weren’t communicating enough to their customers, both internal and external, and weren’t sufficiently prepared for storm responses. 

Avista set about determining how they could improve. They landed on the idea that perhaps they could look at historical weather data to create a predictive model that would alert them when storms were coming and help them figure out key information ahead of time. For example, they could indicate certain storm thresholds (small, medium, large) and get help figuring out what resources they would need and how long an incident response would take.

“Being able to have that information ahead of time, we can begin proactively communicating with our customers to let them know we may experience outages, making sure they're prepared, and then also just having our internal resources ready to go once these events happen.”
Andrew Barrington
Products and Services Manager, Avista Utilities



They developed a prediction model with AiDash Climate Risk Intelligence System™ (CRIS), based on 20 years of historical weather data. 

Avista was already working with AiDash for its IVM (using AiDash Intelligent Vegetation Management System™, or IVMS). As such, AiDash already had images of all of the trees around their distribution and transmission lines. 

Avista wondered if they could then take open-source weather data, filter it with historical outage data that services their region, and then build a predictive model. Such a model would tell them when a certain tree may fall and disrupt power lines, or when they might experience equipment failures.

So, they launched an MVP pilot with AiDash CRIS. They sent 20 years of historical storm data to AiDash. The data was specific — like how a 50-mph windstorm from the northeast looks different from one from the southwest, and the difference between wet snow and heavy snow.

The utility developed thresholds to aid in evaluating the collective outage risk within specific service areas. They needed to predict storm impact and estimate storm-related incidents for 72, 48, 24, 12, and 6 hours prior to any storms. And they did so for each of the 12 offices in their service territory. 

That in turn enabled Avista to determine what sort of response time they could manage for any weather-related incident, how many incidents they could handle in a given amount of time, what resources a response would require, and when and how they would need to call in additional help.

In the pilot, AiDash delivered predictions with an accuracy greater than 80%. After that success, Avista signed a 3-year contract with AiDash and is now in a production environment.  



By being proactive instead of reactive, Avista reduced restoration times, improved customer satisfaction, and minimized staff time during days-long restorations.

Instead of chasing storm-caused incidents and restoring outages as fast as they could, Avista uses CRIS to stay ahead of them. With CRIS, they can reliably predict how many incidents may happen during a major storm, and therefore how many customers would experience outages. And because they get those predictions per office, they can take tactical action ahead of time.

In one major windstorm in January 2024, AiDash predicted 163 of the 177 actual incidents Avista customers experienced (92% accuracy).

Because Avista has this information ahead of time, they can begin proactively communicating with customers about possible outages, making sure they’re prepared, and having their internal resources ready to go once those events happen.

Benefits that Avista has gained from AiDash CRIS include:

  • Improved operational efficiency (minimized need for one person to monitor weather and make decisions and gained better advance understanding of impacts on service territories).
  • Decreased estimated restoration time (ERT) (achieved better planning and prep, getting the right resources in the right place at the right time).
  • Improved corporate awareness and better communication across internal teams.
  • Reduced costs.
  • Improved SAIFI and SAIDI.

To learn more about how Avista used AiDash CRIS to improve their customer experience through AI-powered weather and incident forecasting, read this blog post

Or get more information about our Climate Risk Intelligence System (CRIS) here.




About AiDash
AiDash is an AI-first vertical SaaS company on a mission to transform operations, maintenance, and sustainability in industries with geographically distributed assets by using satellites and AI at scale. With access to a continual, near-real-time stream of critical data, utilities, energy, transportation, water and wastewater, and other core industries can make more informed decisions and build optimized long-term plans, all while reducing costs, improving reliability, and achieving sustainability goals. To learn more about how AiDash is helping core industries become more resilient, efficient, and sustainable, visit

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