Back

Good question. I've tested variations of this across small-to-mid workloads (1k–50k events/month) where the stack actually makes a difference to cost and control.For Google/enterprise-scale (millions of ops), they already have:Infra teams managing Kubernetes clusters and internal toolingNegotiated volume discounts with OpenAI/Anthropic that individuals can't getComplex compliance/security requirements that favor building in-house anywaySo the value prop shifts at that scale.Where this wins (and where I focus):AI agencies building for 10–100 clients (need predictable TCO per client)SMB/mid-market teams (1k–50k monthly volume) where per-step billing compounds fastRegulated verticals (real estate, healthcare, legal) where audit logs and evaluators aren't optionalThe Hugging Face community already uses a lot of this (self-hosted models, caching, routing), but most AI agencies still default to Zapier + GPT-4 for everything because it's fast to prototype—then they hit cost walls at scale.