The startup develops a cloud-managed platform that integrates smart sensors and machine learning analytics to monitor the health of unmonitored industrial machines. This technology enables asset-intensive industries to minimize unplanned downtimes and reduce energy consumption by providing actionable insights from operational data.
Funding
$4M 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.
Founders
Product
Problem
Many industrial assets, particularly those considered "balance of plant" equipment, lack adequate monitoring, leading to unplanned downtime, reduced efficiency, increased maintenance costs, and potential environmental risks like methane leaks. Traditional asset performance management (APM) solutions are often too expensive, complex, and require specialized expertise, making them impractical for widespread deployment.
Solution
Shoreline AI offers a cloud-managed APM platform that simplifies industrial asset monitoring and predictive maintenance. The platform utilizes self-installing, wireless smart sensors that connect directly to the cloud, eliminating the need for gateways or specialized IT infrastructure. A library of over 30,000 pre-built asset physics models automatically provisions the system, enabling real-time condition monitoring and machine-specific analytics. The AI/ML-powered platform provides actionable insights for predictive maintenance, operational optimization, and emissions monitoring, accessible through a user-friendly interface. Shoreline AI's solution helps companies improve asset reliability, reduce maintenance costs, optimize operations, and minimize their carbon footprint.
Target Audience
Shoreline AI targets asset-intensive industries, including oil & gas, renewable energy, manufacturing, chemicals, pharmaceuticals, food & beverage, pulp and paper, primary metals, building materials, defense, HVAC systems, and water/wastewater.
Features
- Plug-and-play wireless sensors for rapid, self-installation and auto-provisioning
- Direct-to-cloud connectivity, eliminating the need for gateways
- Pre-built library of 30,000+ asset physics models for automated system configuration
- AI/ML-powered analytics for real-time condition monitoring and predictive maintenance
- Methane leak detection capabilities for emissions monitoring and compliance
- Cloud-native platform for remote access, scalability, and integration with existing systems
- Mobile app for convenient access to asset health information and alerts
- Integration with CMMS systems
- Generative AI virtual assistant for natural language queries and data synthesis