Urbint, a startup developing AI-powered solutions for infrastructure and utility safety, today announced it has raised a $20 million round. The company will use the capital to scale products and expand into new markets and countries, with the goal of delivering “quantifiable” improvements in worker well-being.

In the early days of the COVID-19 pandemic, energy companies around the U.S. were forced to send workers home to reduce the spread of infection. This exacerbated many of the industry’s longstanding challenges, like how to minimize risks from severe weather, aging infrastructure, and workforce turnover while identifying threats that could cause high-consequence outages to facilities like hospitals and nursing homes.

Urbint taps AI to anticipate and prevent catastrophic power failures, with models of the world and machine learning that enable risk-driven decision-making. Its Lens for damage prevention product incorporates per-incident algorithmic risk scoring, and it performs analyses of areas where high damage is likely to occur on a given day of the week. Lens also offers a holistic view of construction projects to reveal hidden potential hazards, with day-ahead occupational risk scores and insights informed by work histories, schedules, and site condition models. Lens also serves as a system of record for job hazard analysis, contractor qualifications, incident management system events, interventions and outcomes, and site inspection logs, making safety information readily available to simplify workflows.

From the Lens dashboard, which is cloud-based and cross-platform, employees can assign, monitor, and document intervention work across their service territories. Lens overlays internal data on worksites, activities, and contractors, with external conditions sourced from Urbint’s proprietary models that account for weather, traffic, air quality, and more. Operators can lean on Lens to predict work call volumes and make staffing and scheduling decisions for emergency response operations. The platform makes daily predictions on call volume for emergency work orders up to seven days in advance, with predictions by geographical areas or service centers.

Lens supports the creation of staffing plans between emergency and scheduled work configured to the labor rules unique to service areas. When predictions of emergency work order volume go beyond the call volume threshold, it automatically notifies supervisors.

Urbint counts among its client base over 40 utilities and asset operators throughout North America, including National Grid, Southern Company, Con Edison, Exelon, Dominion, NiSource, and Xcel Energy. For one utility company with more than 3.6 million electric and 2 million natural gas customers across several states, Urbint claims its 14-day daily call volume predictions for nine service territories are consistently 85% accurate.

Energy Impact Partners and Piva co-led the investment in New York-based Urbint, with Salesforce Ventures and National Grid Partners participating. It’s possible a portion of its fundraising will support future acquisitions and mergers, though the 70-person company declined to comment. In October 2019, Ubint acquired Opvantek, a rival provider of risk-based asset management solutions for gas, electric, and telecommunications utilities.

Some utilities are employing AI and machine learning to address the windfalls and fluctuations in energy usage resulting from the pandemic. Early evidence suggests load forecasting could ensure operations aren’t interrupted in the coming months, thereby preventing blackouts and brownouts. This might also bolster the efficiency of utility companies’ internal work processes, leading to reduced prices and improved service long after the pandemic ends.

“Our vision is to build a world of zero safety incidents in the field,” said Urbint founder and CEO Corey Capasso. “In a time of aging infrastructure, climate change, and unprecedented challenges like the coronavirus pandemic, we’re seeing more and more utilities and infrastructure operators turn to artificial intelligence to reduce risk. This new funding will accelerate the development of our technology to enhance field worker safety and fuel our expansion into new verticals and geographies.”

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