Netomi's three lessons for scaling agentic systems into the enterprise

Netomi distilled three lessons for scaling agentic systems into the enterprise: GPT-4.1 handles low-latency tool calls, GPT-5.2 handles multi-step planning, and both run inside a governed execution layer. Its concurrency framework maintained sub-3-second responses and 98% intent classification accuracy during DraftKings event traffic peaks exceeding 40,000 concurrent customer requests per second. The governance layer includes inline schema validation, policy enforcement, PII protection, deterministic fallback, and runtime observability.