Data Pipeline Portfolio

Ten production data pipelines built for clients across e-commerce, real estate, finance, and business intelligence. Each project is a complete system: scraping collects the raw data, ML or classification logic structures and scores it, and automation routes it to where decisions actually happen.

The industries covered: e-commerce price and competitor intelligence, real estate acquisition research, financial services document extraction, telecom AI, and B2B operations. Scale varies — some pipelines process thousands of records daily, others handle millions. Some run on a schedule; others are real-time.

Each case study frames the problem as a business metric first: hours eliminated, accuracy achieved, ops overhead reduced. Then covers the architecture and what runs in production. Client names are mostly withheld by agreement. The metrics are real.