Structured previously unused event data into query-ready AI signal
Millions of impression and behavioral events were flowing through a major retailer's infrastructure — completely unused. The engineering team knew the data was valuable but had no bandwidth to build the pipeline. A Grafter embedded with the data engineering team and built a real-time Kinesis→Redshift pipeline while capturing the architecture pattern as an Enterprise Skill.
High-value event data flowing through the system unused. No internal bandwidth. No clear architecture pattern to hand off.
Grafter identified the event stream, built the ingestion and normalization layer, and packaged the full architecture as a reusable Skill for the data engineering team.
Packaged, tested, and left behind for the internal team to run and extend independently — no ongoing dependency on CodeVine.