Waterson Technologies develops real-time, AI-powered software for monitoring water biological quality, utilizing data from physicochemical sensors to predict contamination risks. This automated solution significantly reduces the time and cost associated with traditional laboratory testing methods, providing immediate insights for water utilities and other industries reliant on safe water.
Funding
$120K 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
Traditional methods of assessing drinking water biological quality rely on grab sampling and laboratory testing, which can take several days to produce results. This delay makes it difficult to respond quickly to contamination events, and the expense of maintaining laboratories, equipment, and trained personnel adds to the cost of water quality monitoring. Unpredictable environmental conditions and aging infrastructure further exacerbate these challenges.
Solution
Waterson Technologies offers real-time, AI-powered software for monitoring water biological quality, providing an early warning system for potential contamination. The system uses data from off-the-shelf physicochemical sensors to predict the probability of biological contamination. Data is recorded in a database, developing customer-specific time-series datasets, which are then cleaned and merged for use by the AI algorithm. The algorithm estimates the probability of biological contamination, and the results are presented visually in a user-friendly interface.
Target Audience
The primary customers include municipal water utilities seeking to avoid water contamination risks and ensure compliance, as well as beverage and food manufacturers needing to guarantee product taste and expiration dates, and other industries such as agriculture, farming, and cosmetics.
Features
- AI algorithm software that predicts the probability of biological contamination using state-of-the-art methodologies.
- Water quality database with millions of labeled data points, constantly updated for algorithm training.
- User interface designed to provide insight into data analytics, delivering real-time, minute-by-minute data individualized for user needs.
- Utilizes data from off-the-shelf physicochemical sensors.
- Customer-specific time series data sets.
- Data cleaning and merging for AI algorithm needs.