DataPond develops an AI powered monitoring system, PathWatch, that enables continuous detection of microbial contamination in surface water such as rivers and lakes. The system analyzes data from common, low cost sensors including turbidity, conductivity, dissolved oxygen, and temperature to detect indicators like E. coli and fecal coliforms.
Using proprietary machine learning models, the platform processes incoming sensor streams to classify contamination risk and provide immediate alerts through a secure cloud based interface. This eliminates the need for manual sampling, lab analysis, or additional hardware installations. By replacing slow and costly testing methods with real time monitoring, DataPond offers water authorities a scalable way to maintain regulatory compliance and protect public health.
Cumulative Funding Raised Over Time ($)
Employees Over Time
DataPond Climate Tech relevance
Over 2 billion people worldwide do not have access to safe water, and Every 2 minutes a child dies from water-related disease- mostly from biologically contaminated water. The UN has defined the supply of safe and affordable drinking water as one of its main targets - as set out in SDG6. The problem gets bigger due to population growth and climate changes.
Current methods for detecting contamination in the water are slow (1-3 days in the lab), expensive, and require professional personnel - therefore the tests are performed at a very low frequency and only in a limited number of locations.
Detecting contamination in time is key to being able to treat it effectively.
Today, there is no other real-time in-situ and low-cost sensor for biological contamination sensing.