Aren provides a patented platform that utilizes computer vision and machine learning to automate the assessment and management of civil infrastructure assets, enabling engineers to quickly identify and quantify damage. This technology addresses the critical issue of infrastructure failures by offering predictive insights and data-driven maintenance schedules, ultimately optimizing repair prioritization and spending.
Funding
$2.7M 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
Civil infrastructure assets are subject to constant deterioration, leading to failures that endanger lives and incur significant costs. Traditional assessment methods are often manual, time-consuming, and costly, resulting in delayed identification of critical issues and inefficient allocation of resources. The lack of proactive and quantitative tools hinders effective infrastructure management and predictive maintenance.
Solution
Aren offers a patented platform that leverages computer vision and machine learning to automate the assessment and management of civil infrastructure assets. The technology enables engineers to quickly identify and quantify damage, track changes over time, and predict future structural changes. By providing actionable insights and data-driven maintenance schedules, Aren optimizes repair prioritization and spending, minimizing the risk of failure. The platform generates high-resolution 3D digital twins of assets, providing engineers with virtual access anytime, anywhere, for enhanced monitoring and analysis.
Target Audience
The primary customers are civil engineers, infrastructure managers, and government agencies responsible for maintaining and assessing bridges, roads, and other critical infrastructure assets.
Features
- Patented AI technology for automated damage detection and quantification
- Predictive analytics to forecast structural changes and deterioration rates
- 3D digital twin generation for virtual asset access and analysis
- Source-agnostic data collection, compatible with standard cameras and drones
- Actionable insights and data-driven maintenance schedules for optimized resource allocation
- Change detection and tracking over time to monitor asset degradation