Transforming regulatory analysis with AI for an industrial facility

About this project

Client
Confidential Client
Location
Minnesota
Completion date
2025

When a long-standing client faced a complex permitting question, they turned to Barr for support. The client wanted to understand how the conditions in a current permit compared with those of other industrial facilities across the state, with a specific focus on water quality standards and designated water bodies. Historically, answering a question like this required a team of staff to manually review and summarize hundreds of individual permits, an intensive and time-consuming process. 

Instead, Barr’s team proposed an innovative approach using an AI-assisted workflow to rapidly extract key information from more than 500 permits across Minnesota. We developed a custom natural language processing workflow to extract the data, creating a searchable database of facility discharge information. The database included permit stations and effluent limits, location data, and whether the facility released to a listed water body. Our GIS team then mapped this data, giving the client a clear view of how their permit compared to others across the region. 

The approach delivered timely, targeted insights and created a foundation the client can reuse to answer future regulatory questions. By combining subject-matter expertise with AI-supported tools, we helped the client gain clarity and context faster and more efficiently than before. 

Key team members

Phillip Fish
Vice President
Senior Chemical Engineer
Tom Holstrom
Senior Environmental Engineer
Kyong Song
Senior Data Scientist
Valerie Venier
Chemical Engineer

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