I build extraction pipelines that monitor competitor catalogs, pull pricing data, capture lead intelligence, and normalize messy web inputs into clean feeds your team can actually use.
Each engagement is structured around stable extraction, output quality, and operational reliability. That means less time babysitting scripts and more time using the data downstream.
Browser automation and direct-request collectors built around the target site’s actual behavior, including pagination, product variants, account flows, and anti-bot tolerance.
Normalization pipelines that map raw fields into consistent schemas, remove duplicates, validate values, and prepare exports for analytics, CRM ingestion, or internal dashboards.
Monitoring and retry strategies so failed jobs surface quickly, partial runs are visible, and data gaps do not silently reach business users.
Operational handoff with documentation covering selectors, dependencies, source assumptions, and how the system should be extended as the target websites evolve.
Competitive intelligence teams use this to track catalog changes, pricing shifts, availability, and market movement without assigning analysts to repetitive browser work.
Sales and operations teams use it to build lead lists, supplier datasets, and recurring structured reports that feed internal systems on a predictable schedule.