Why the Next Era of AI Is About Infrastructure, Not Just Models

9 hours ago

The evolution of AI in enterprises has shifted from initial experimentation to production, with concerns now focusing on ROI, cost, and data governance.
Production AI requires reliability, auditability, cost control, and governance, highlighting the need for infrastructure rather than just models.
Recent changes include increased adoption velocity leading to fragmentation, cost opacity, and governance gaps as AI expands across sectors.
Managing multiple AI providers creates operational complexity with custom failover, spreadsheets for cost tracking, and manual tuning, which is unsustainable.
Cost visibility is critical; teams need to compare cost-per-outcome and set policies to manage spending effectively as AI scales.
Control over AI infrastructure is becoming the new competitive advantage, emphasizing intelligent routing, observability, and policy enforcement.
Mozilla built Otari as an open-source control plane to provide visibility, governance, and flexibility, addressing consolidation and opacity in AI systems.
The agentic era requires systems to coordinate many AI agents, increasing complexity and necessitating a foundational control layer for scalable deployments.
Otari aims to define a new category of AI infrastructure, enabling organizations to own their stack and avoid vendor lock-in in critical industries.

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