HazardMapper

Overview

An NLP prototype that maps safety observations into standardized risk categories to support trend analysis and preventative action.

Goals

• Standardize free-text safety observations into consistent risk categories.
• Enable trend analysis across large volumes of observations.
• Support earlier, preventative action.

Approach

• Build an NLP/LLM pipeline to classify observations into a taxonomy.
• Evaluate categorization quality against human-labeled samples.
• Aggregate categorized data for trend reporting.

Status

🚧 In progress. A full write-up — methodology, results, and code — is coming soon.