# Why One Model Is Never Enough: Routing Incident Analysis With cascadeflow
The first time our incident assistant burned through a premium reasoning model to parse a three-line nginx log, I knew we had a problem. Not with the AI. With the assumption that one model, called blindly every time, is the right way to build anything production-worthy.
That assumption is expensive. And in the context of real-time incident response—where you're getting paged at 2 AM and your Redis cluster is throwing connection errors—it's also slow in ways that hurt.
This is the story of how I built IncidentOS, an AI-powered operational memory system for SRE teams, and why cascadeflow became the piece that made the runtime actually usable.
What IncidentOS Actually Does
