Urbint is an AI platform that utilizes real-world data to predict and assess risks to workers and critical infrastructure, enabling proactive safety measures and damage prevention. By identifying high-risk scenarios in advance, Urbint helps energy, telecom, and infrastructure companies reduce incidents and protect their communities.
Funding
$140M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
SVFounders
Product
Problem
Energy, telecom, and infrastructure companies face significant risks to worker safety, asset damage, and service disruptions due to excavation accidents, natural disasters, and other unforeseen events. Traditional risk assessment methods often rely on lagging indicators and manual analysis, limiting the ability to proactively identify and mitigate potential hazards. This can lead to increased incidents, higher operational costs, and potential harm to communities.
Solution
Urbint offers an AI-powered risk assessment platform that leverages real-world data to predict and prevent incidents impacting worker safety and critical infrastructure. By integrating historical incident data, infrastructure characteristics, and external factors like weather patterns and construction activity, Urbint identifies high-risk scenarios in advance. The platform provides actionable insights, enabling companies to proactively allocate resources, implement targeted safety measures, and reduce the likelihood of damages and service interruptions. Urbint's solutions cover worker safety, damage prevention, and storm response, offering a comprehensive approach to risk management across various infrastructure categories.
Target Audience
Urbint primarily serves gas, electric, oil and gas, telecom, and cable utilities, as well as other infrastructure companies seeking to improve safety, reduce damages, and enhance operational resilience.
Features
- AI-driven risk scoring that identifies the most damage-prone excavation sites.
- Predictive analytics that assess the likelihood of incidents based on a combination of internal and external data sources.
- Integration of historical incident data, infrastructure characteristics, weather patterns, and construction activity.
- Identification of potential no-call-in excavation damages by leveraging permit data and natural language processing to identify habitual offenders.
- Risk assessment for worker safety, focusing on hazards most likely to lead to injuries.
- Storm response solutions that connect the entire natural disaster lifecycle in one platform for logistics, emergency work management, and resource allocation.
- Customizable dashboards and reporting tools for visualizing risk and tracking the effectiveness of mitigation efforts.