Transforming Environmental Data Analysis with AI

The Challenge:
The Omgevingsdienst Midden- en West-Brabant (OMWB) handles vast amounts of environmental measurement data. Previously, analysts spent many hours transferring raw data into Excel, manually performing calculations and creating graphs. This manual process was slow, repetitive and prone to human error, limiting the agency’s ability to quickly identify patterns or anomalies in the data.

The Solution:
SevenLab built an AI-driven analysis tool that automates the entire workflow from data ingestion to reporting. The key features include:

• Automated data processing: Raw measurement files are ingested and processed automatically, eliminating manual transfers.

• Anomaly detection: Intelligent algorithms identify deviations and anomalies in the data that might signal environmental issues.

• Automated reporting: The system generates comprehensive reports with visualizations, including graphs and trend analyses.

• No more Excel: All steps are performed within the tool, removing the need for external spreadsheets.

Results and Impact:

• Reduced repetitive work: Staff no longer spend hours on manual data handling, freeing time for higher-value activities.

• Faster insights into patterns: Automated analysis delivers quick identification of trends and outliers.

• Focus on interpretation and decision-making: With the grunt work automated, analysts can focus on understanding results and making informed decisions.

• Increased accuracy: Automation reduces human errors, enhancing the reliability of environmental insights.