NativelyAI continuously monitors runtime behavior across latency, cost, throughput, and reliability signals. These metrics feed back into orchestration decisions, enabling adaptiveoptimization over time.
For example:
frequently invoked workflows may be restructured for lower latency,
expensive inference paths may be replaced with more efficient alternatives,
infrastructure placement may shift based on load or cost changes.
Importantly, optimization never violates policy constraints. Performance improvements are bounded by governance rules defined at the organizational level.
This creates systems that improve automatically without becoming unpredictable.
