Urbint, a startup that develops AI-based solutions for infrastructure and supply security, announced today that 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 aim of achieving "quantifiable" improvements in the well-being of employees.
In the early days of the COVID-19 pandemic, energy companies were in the United States forced to send workers home reduce the spread of infection. This exacerbated many of the longstanding challenges in the industry, e.g. For example, minimizing risks from severe weather, aging infrastructure and staff turnover, while identifying threats that can lead to the failure of facilities such as hospitals and nursing homes with high consequences.
Urbint uses AI to anticipate and prevent catastrophic blackouts. World models and machine learning enable risk-driven decisions. The Lens for Damage Prevention product includes an algorithmic risk assessment per incident and analyzes areas where high damage is likely to occur on a particular day of the week. Lens also provides a holistic view of construction projects to uncover hidden potential threats. The lens also serves as a recording system for analyzing work hazards, qualifying contractors, events, interventions and results from the incident management system, as well as logs for site inspection, making safety information readily available to simplify workflows.
Employees can assign, monitor and document intervention work in their service areas via the lens dashboard, which is cloud-based and cross-platform. The lens overlays internal data on construction sites, activities and contractors with external conditions that come from Urbint's own models that take weather, traffic, air quality and more into account. Operators can rely on Lens to predict work call volume and make personnel and planning decisions for emergency response. The platform creates daily call volume forecasts for emergency work orders up to seven days in advance with geographic area or service center forecasts.
Lens supports the creation of personnel plans between emergency and planned work, which are configured according to the work rules specific to service areas. When the emergency order volume predictions exceed the call volume threshold, managers are automatically notified.
Urbint's customers include over 40 utilities and plant operators across North America, including National Grid, Southern Company, Con Edison, Exelon, Dominion, NiSource and Xcel Energy. For a utility with more than 3.6 million electricity and 2 million natural gas customers in several states, Urbint claims that the daily 14-day call volume forecasts for nine service areas are consistently 85% accurate.
Energy Impact Partners and Piva jointly led the investment in Urbint, New York, in which Salesforce Ventures and National Grid Partners participated. Part of the fundraising may support future acquisitions and mergers, although the 70-member company declined to comment. In October 2019, Ubint acquired Opvantek, a competing provider of risk-based asset management solutions for gas, power and telecommunications companies.
Some utilities are using AI and machine learning to address the gusts of wind and fluctuations in energy use caused by the pandemic. Early evidence suggests that load forecasts could ensure that operations will not be interrupted in the coming months, thereby preventing blackouts and outages. This could also improve the efficiency of utilities' internal work processes and lead to price cuts and improved service long after the pandemic ended.
"Our vision is to build a world without local security incidents," said Corey Capasso, founder and CEO of Urbint. “In an age of aging infrastructure, climate change, and unprecedented challenges such as the coronavirus pandemic, more and more utilities and infrastructure managers are turning to artificial intelligence to reduce risk. This new funding will accelerate the development of our technology to improve the security of the sales force and drive our expansion into new industries and regions. "