LivNSense Technologies offers an AI-based platform, GreenOps™, that utilizes machine learning and digital twin technology to monitor and optimize greenhouse gas emissions in energy-intensive industries. The platform enables real-time data analysis and predictive insights, achieving up to 25% reductions in GHG intensity and significant energy cost savings for its clients.
Funding
$3.8M 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
Energy-intensive industries face increasing pressure to reduce greenhouse gas (GHG) emissions and improve energy efficiency, but lack comprehensive tools for real-time monitoring, analysis, and optimization of their complex processes. Traditional methods often rely on lagging indicators and manual data collection, hindering proactive decision-making and the achievement of net-zero targets.
Solution
LivNSense Technologies offers GreenOps™, an AI-powered SaaS platform that leverages machine learning and digital twin technology to enable deep decarbonization in energy-intensive industries. GreenOps™ provides real-time data acquisition from heterogeneous sources, combined with intuitive analytics and predictive insights to optimize energy balancing and reduce GHG emissions. The platform employs science-based AI/ML models to benchmark CO2 emissions, analyze energy efficiency, and recommend carbon offset strategies. By creating a digital twin of industrial processes, GreenOps™ delivers prescriptive recommendations for improved energy consumption, reduced risks, and enhanced profitability.
Target Audience
The primary target audience includes energy-intensive industries such as manufacturing, oil and gas, and mining, particularly Fortune 500 companies seeking to reduce their carbon footprint and improve energy efficiency.
Features
- Real-time data acquisition from diverse sources, including sensors and existing plant systems
- Hybrid AI/ML models for predictive analytics and CO2 benchmarking
- Digital twin technology for simulating and optimizing industrial processes
- Carbon Cockpit for visualizing GHG emissions and tracking reduction progress
- ESG-Safety Compliance module for monitoring and reporting environmental and safety metrics
- Integration of material science, combustion, and energy efficiency models
- Patented CO2 Benchmarking & Optimization technology