Updates on production AI systems, engineering practice, recent technology, and company work from the Vincere.dev team.
A practical blueprint for ingesting, chunking, retrieving, evaluating, and operating RAG over large document collections.
A field guide to the moving parts that make RAG reliable beyond the demo: retrieval, reranking, guardrails, observability, and evals.
Enterprise RAG needs refusal behavior, confidence signals, and evidence thresholds so the system can avoid unsupported answers.
A diagnostic guide to why RAG systems still hallucinate in production, mapping each failure mode to its root cause and the fix that actually addresses it.
Practical lessons from building a healthcare data warehouse automation platform that supported 100+ pipelines with a 3-5 person data team.
We help teams design, deploy, and operate RAG systems, AI workflows, and data infrastructure in real business environments.
