Customer Service Automation
Enterprise AI agents needed to coordinate messy, high-volume service workflows across many backend systems while staying low-latency, policy-compliant, and predictable under real production load.
Reported impact
Netomi created a blueprint for agentic enterprise systems that stay responsive under burst traffic, keep policy controls inline, and scale safely across demanding customer-service and regulated workflows.
Netomi built an Agentic OS that combines OpenAI GPT-4.1 and GPT-5.2 inside a governed execution layer for production-grade enterprise agents. GPT-4.1 handles low-latency tool use and fast reasoning for transactional workflows, while GPT-5.2 takes on deeper multi-step planning and complex orchestration. The runtime is designed for ambiguity: requests can span booking engines, loyalty databases, CRMs, payments, policy logic, and knowledge sources, so Netomi uses structured planning, persistence reminders, explicit tool-use expectations, and rich-media decisions to keep state across long tasks. The company also architected the platform for concurrency rather than serial pipelines, allowing it to sustain sub-three-second responses during traffic bursts such as major sporting events. Governance is intrinsic to execution, with schema validation, inline policy enforcement, PII protection, deterministic fallback, and full observability so agent behavior remains auditable in regulated settings like insurance and travel.
Customer requests are classified and routed through the Agentic OS, which calls backend systems such as CRMs, booking engines, payments, and policy services in parallel. GPT-4.1 or GPT-5.2 then reasons over the results, while governance checks validate tools, enforce policies, mask PII, and back off to safe paths if confidence drops.
"DraftKings ... with traffic during major sporting events spiking above 40,000 concurrent customer requests per second"
"Netomi has sustained sub-three-second responses with 98% intent classification accuracy"
"The governance is not bolted on—it’s part of the runtime."
"Their platform pairs GPT‑4.1 for low-latency, reliable tool use with GPT‑5.2 for deeper, multi-step planning"
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Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
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