In-depth architectural critiques, evaluation frameworks, and lessons learned from engineering production AI systems. Written by our systems architects.
An architectural critique of autonomous agent loops in production systems. Why deterministic state machines, static DAGs, and typed code should remain the default for enterprise workflows.
A technical deep dive into designing low-latency, cross-modal systems combining vision-language models, spatial coordinate grounding, and hybrid vector retrieval.
A rigorous methodology for measuring, quantifying, and mitigating hallucination rates in production AI systems through automated golden evaluation harnesses.
Why standard chunk-and-embed RAG architectures break down on complex enterprise queries, and how multi-step agentic knowledge exploration bridges the gap.
Overcoming stream instability, camera calibration drift, hardware latency bottlenecks, and edge failover in 24/7 production video analytics.