The world’s most advanced water organizations trust Aquatic Informatics to achieve higher data integrity, defensibility, compliance, timeliness, and reporting.
From source water through to the receiving environment, our interconnected data management platforms drive the efficient management of water information across the water cycle to protect human health and reduce environmental impact.
Consolidate disparate data sources and systems into a unified platform for efficient management.
Easily display and correct integrated data sources for compliance reporting with a defensible audit trail.
Make faster decisions with real-time insights, powerful contextual visualization tools, and interactive online access for consumers.
Aquatic Informatics provides software solutions that address critical water data management, analytics, and compliance challenges for the rapidly growing water industry.
Aquatic Informatics empowers the water industry across all applications, helping to transform data into actionable, timely insights.
Our latest development for Aquarius, HydroCorrect is a new automated data validation tool that can power proactive monitoring and management of groundwater, flooding, and water quality in the Aquarius platform.
Announcing the launch of Rio, the next generation in cloud-based compliance and operations data management solutions for water and wastewater utilities.
One of the world’s largest water data management companies with over 100 billion real-time field measurements helping to protect our water quality, infrastructure and communities.
Aquatic Informatics is a mission-driven software company that organizes the world’s water data to make it accessible and useful. With four major software platforms, and more than 1,000 customers in 60 countries, Aquatic Informatics provides infotech solutions for all water resources, including source water, drinking water, municipal and industrial wastewater, and the receiving environment. Their platforms address analytical and compliance needs for managing large volumes of data.