Netomi’s lessons for scaling agentic systems into the enterprise

Netomi’s lessons for scaling agentic systems into the enterprise

Built with OpenAI GPT‑4.1 and GPT‑5.2, Netomi provides a blueprint for scaling safe, predictable agentic systems across the enterprise. The company serves Fortune 500 customers like United Airlines and DraftKings, demonstrating successful agentic AI deployment.

Enterprises require AI agents to reliably handle complex workflows, adhere to policies, maintain performance under load, and provide transparency; existing AI systems often struggle with real-world variability and brittle flows, leading to failures and significant costs.

Key Insights

• GPT-4.1/GPT-5.2 combination, 2026: Netomi pairs GPT-4.1 for low-latency, reliable tool use with GPT-5.2 for deeper, multi-step planning.
• Concurrency over sequential processing: Netomi designed for concurrency, leveraging streaming and stable tool-calling of GPT-4.1 to improve system responsiveness.
• Governance as runtime component: Netomi’s governance mechanisms, including schema validation and PII protection, are integrated directly into the runtime for trustworthy AI.

Working Example

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Practical Applications

• Use Case: DraftKings uses Netomi to handle over 40,000 concurrent customer requests per second during major sporting events, maintaining sub-three-second response times.
• Pitfall: Building sequential AI systems (classify → retrieve → validate…) leads to latency and potential failure under high load; concurrency is essential for scalability.

References:

• https://openai.com/index/netomi/