This case study is about a Dallas-based digital health company that needed an automated way to analyze 23 years of SEC 10-K filings to track corporate technology investments and risk exposures. The solution delivered a four-phase NLP and automation pipeline, covering data scraping, keyword-based risk extraction, econometric modeling, and visualization, which confirmed hypotheses on how data center risk exposure influences corporate performance and investor risk pricing.
