Cobalt Water Global provides the N2ORisk DSS, an AI/ML platform designed for water utilities and industries to manage wastewater N2O process emissions. This solution enables users to quickly account for, monitor, and reduce nitrous oxide greenhouse gas emissions through data upload and analysis. The platform offers a cost-effective approach to achieving significant N2O reductions, up to 90%, by mimicking expert reasoning processes.
Funding
$220K 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
Wastewater treatment plants are significant sources of nitrous oxide (N2O) emissions, a potent greenhouse gas, but current methods for accounting for and mitigating these emissions are often inaccurate and costly. Generic emission factors and uncalibrated mechanistic models fail to capture site-specific process conditions, hindering effective reduction strategies.
Solution
Cobalt Water Global offers the N2ORisk DSS, an AI/ML platform designed to help water utilities and industries accurately account for, reduce, and continuously monitor N2O emissions from wastewater treatment processes. The platform uses site-specific process data and machine learning to provide science-based estimates of N2O emissions, identify reduction opportunities, and generate dynamic risk profiles. By integrating AI with process knowledge, the N2ORisk DSS enables users to prioritize sites for measurement and mitigation, implement control actions, and track progress toward net-zero goals. The platform supports the entire N2O reduction journey, from initial accounting and assessment to ongoing monitoring and process optimization.
Target Audience
The primary target audience includes water utilities and industries seeking to reduce their greenhouse gas emissions and improve the sustainability of their wastewater treatment processes.
Features
- AI/ML-driven platform for accounting, reduction, and monitoring of wastewater N2O process emissions
- Site-specific N2O emission estimates based on process data and machine learning, replacing generic emission factors
- Dynamic risk profiling to identify N2O production drivers and reduction opportunities
- Integration of knowledge-based AI with process data for accurate emission predictions
- Capability to train site-specific machine learning models with measured N2O data
- Continuous process and N2O emissions monitoring to ensure sustained reductions
- Monthly emissions reports for tracking progress toward net-zero goals