Insights
Analysis and perspective on enterprise AI, data engineering, governance, and the systems that connect them. Written by practitioners, not pundits.
Our audit of a Fortune 200 manufacturer uncovered 340+ unsanctioned AI tools with annual spend exceeding $2.8M. The real cost wasn't the subscriptions — it was the unvetted data leaving the org through prompt windows. Here's the governance playbook we built to regain control without killing innovation.
Retrieval-augmented generation demos are easy. Production RAG that handles ambiguous queries, stale embeddings, and compliance constraints across regulated industries is a different discipline entirely. We break down the architecture patterns, chunking strategies, and evaluation frameworks that held up past month one.
When two mid-market insurers merged their claims platforms, schema drift nearly derailed the integration. Introducing data contracts — versioned, tested, producer-owned interface agreements — cut reconciliation errors by 92% in eight weeks. A detailed look at the contract specification, CI enforcement, and organizational change that made it work.
Most enterprise AI strategies stall at the pilot stage because they optimize for model accuracy instead of decision velocity. We introduce the Decision System Canvas — a framework that maps AI capabilities to specific business decisions, identifies data dependencies, and defines rollback conditions before a single line of code is written.
A global logistics company had 23 teams deploying through a shared Jenkins monolith with a two-week queue. We designed a self-service platform layer — golden paths, automated compliance gates, ephemeral environments — that gave teams autonomy while maintaining security and auditability. Here's the architecture and adoption strategy.
Your VPC rules are airtight, but an analyst with broad Snowflake access just exported 2M customer records to a personal S3 bucket. We walk through implementing attribute-based access control, column-level masking, and real-time lineage tracking that enforce zero-trust principles at the data layer — not just the network edge.
