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Damage Prevention

Insights for Damage Prevention

AI Models Trained on Millions of Data Points Deliver Powerful Insights for Damage Prevention

Without AI-powered insights and platforms, damage prevention professionals manually juggle thousands of 811 tickets and don’t have the insight to connect the dots for which excavations should be prioritized due to the higher likelihood of an incident occurring and the potential impact of that incident.

Irth processes more one call tickets across North America than any other company. We have more and better data to train our AI models to fit the needs of each industry we serve. Our customers can combine their historical and industry-wide risk factors to gain the most useful insights. We retrain all our AI models every day, ensuring they continue improving based on new data.

But that data means nothing if you can’t understand it. Irth Insights for Damage Prevention enables understanding. Delivering more than 50 million insights each year, it tells a story based on each ticket’s risk profile using natural language, making it easy to understand what actions they should take to reduce damages.

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Powerful AI/Machine Learning

AI/machine learning power our insights and build intelligence over time to drive the next best action for each 811 ticket.

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Automatic Damage Risk Analysis

Leverage automatic analysis of your tickets and damage data to quantify and qualify the level of risk to your assets.

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Reliable Risk Scoring

Improve your damage prevention program with our risk scoring system and Smart Score, which have contributed to a more than a 30% reduction in damages for some of our clients.

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Decrease Operational Costs

By using AI to understand the complexity of the locate, you can ensure the right resources are assigned to the task, saving time and money.

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Reduce Damages

With AI, machine learning, and automation driving processes, notifications, prompting field visits, and follow-up, damages are reduced.

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Prioritize Next Best Action

Accurately discern where to prioritize activities because AI-based risk scoring combines previous damage history with generic risk factors to give you a more refined risk assessment.

Routing and Assigning 811 Tickets

Increase productivity and streamline ticket management by always assigning the right person at the right time to the right ticket with dynamic routing for 811 tickets.

Automatically configure your locators’ schedules and starting locations using ESRI for fleet management.

By analyzing data from diverse sources, including nearly any element of an 811 ticket, geography, registration code, ticket type, and more, to route the ticket, the number of tickets that require manual intervention is reduced.

Customers can choose a build-it-yourself approach or allow Irth’s dynamic routing module to optimize the assignment and routing of tickets based on nearly any criteria, including user OQ status, location, proficiency, ticket data, and more.

Dynamically routed tickets are automatically displayed in the mobile application, allowing each locator to know what they need to work on and when.

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Damage Prevention - Route Planning

811 Ticket Risk Scoring

Our industry-leading AI engine analyzes and identifies an 811 ticket’s likelihood of an incident and potential impact, driving your damage prevention efforts.

 

Irth’s machine learning model analyzes risk criteria and damage data to produce an Insights AI score (incident likelihood percentile) for each ticket.

Irth uses a large language model (LLM) to create a readable risk reason from the Insights AI score explaining the “why” behind the score in easy-to-understand language.

When you can understand the risk of a ticket, you can take better actions to reduce damages.

 

 

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Damage Prevention - Risk Score

811 Ticket Screening

AI powers our 811 ticket screening centers, allowing users to make an educated decision when dispatching tickets.

Fully configurable to your needs, allowing you to define your criteria or leverage Irth’s AI clearing model to screen tickets.

AI can consider variables such as excavator name, work type, work done for, proximity to facilities, facility location, ticket type, and many more to assign or clear tickets just like a human would. 

AI can assess the complexity of the locate to ensure the right resources are assigned to the task.



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Damage Prevention - Dig Site

Locate Ticket Audits

Irth Insights uses machine vision to automatically screen locate photos tied to 811 tickets, enabling users to process hundreds to thousands of tickets that are received. 

AI-powered image analysis identifies if the correct flag and paint colors were used for the location, as well as whether the distance of the photo from the dig site meets the users requirements. 

Each photo is reviewed by Irth Insights and each ticket is audited and automatically assigned a pass or fail per the user's requirements.

Irth Insights provides users the ability to process a vast number of 811 tickets, thereby reducing errors and ensuring asset safety.



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Meter Inspections

Irth Insights uses machine vision to automatically detect and classify issues at meter locations, enabling users to process inspection data at scale efficiently.

AI-powered image analysis identifies signs of corrosion, buried meters, or vegetation interference. Field technicians simply capture a photo of each meter, and Irth Insights automatically displays the probability of these conditions for each work item.

Users can set thresholds to determine whether a corrective action is triggered or if the inspection is marked complete. If conditions meet or exceed the set thresholds, Irth Insights will either initiate the next logical corrective step or close the current inspection, scheduling the next one accordingly.

Irth Insights empowers users to streamline meter inspections, reduce manual review, and ensure regulatory and safety compliance across their network.



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Training & Operator Qualifications

Deliver targeted, on-demand employee training and education to drive safety, promote continuing education, and meet organizational learning objectives.

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