Netomi’s lessons for scaling agentic systems into the enterprise

Enterprises expect AI agents to handle messy workflows reliably, honor policies by default, operate under heavy load, and show their work.

Netomi⁠⁠(opens in a new window) builds systems that meet that high bar, serving Fortune 500 customers like United Airlines and DraftKings. Their platform pairs GPT‑4.1 for low-latency, reliable tool use with GPT‑5.2 for deeper, multi-step planning, running both inside a governed execution layer designed to keep model-driven actions predictable under real production conditions.

Running agentic systems at this scale has given Netomi a blueprint for what makes these deployments work inside the enterprise.

“Our goal was to orchestrate the many systems a human agent would normally juggle and do it safely at machine speed.”

Puneet Mehta, CEO

Lesson 1: Build for real-world complexity, not idealized flows

A single enterprise request rarely maps to a single API. Real workflows span booking engines, loyalty databases, CRM systems, policy logic, payments, and knowledge sources. The data is often incomplete, conflicting, or time-sensitive. Systems that depend on brittle flows collapse under this variability.

Netomi designed its Agentic OS so OpenAI models sit at the center of a governed orchestration pipeline built for this level of ambiguity. The platform uses GPT‑4.1 for fast, reliable reasoning and tool-calling—critical for real-time workflows—and GPT‑5.2 when multi-step planning or deeper reasoning is required.

To ensure consistent agent behavior across long, complex tasks, Netomi follows the agentic prompting patterns recommended by OpenAI:

Together, these patterns help the model reliably map unstructured requests to multi-step workflows and maintain state across discontinuous interactions.

With GPT‑4.1 and GPT‑5.2, Netomi can keep extending these patterns into richer multi-step automations—using the models not just to answer questions, but to plan tasks, sequence actions, and coordinate the backend systems a major airline depends on.