This engagement involved consulting for a cloud-compliance and analytics company in the In-Q-Tel portfolio, focused on automating compliance audits for sensitive cloud workloads.

My work centered on making compliance evidence usable at scale: building data pipelines and warehouse structures that could capture scan outputs, preserve lineage, and support analysis and reporting over time. The concrete implementation work included AWS Glue/Spark-style processing and S3-backed storage patterns, and it fits the broader theme of “make the system auditable without making it slow.”

The company name is not disclosed publicly here, but the shape of the work matters: compliance work only becomes practical when evidence is structured, repeatable, and visible to the people who need to make decisions.