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One Intelligence (1-i.ai) Launches AI Control Plane to Help Enterprises Build and Operate Production AI

Unified platform accelerates AI application development while delivering governance, routing, and cost visibility by default.

The core idea behind 1-i is simple: Build AI like infrastructure. Run AI like infrastructure. While Prompt engineering is where AI starts, infrastructure is where AI scales.”
— Deepesh Desai, Founder of 1-i.ai.

ANN ARBOR, MI, UNITED STATES, March 16, 2026 /EINPresswire.com/ — One Intelligence ( 1-i.ai ) today announced the launch of its AI Control Plane, a unified platform designed to help enterprises build, publish, and operate production AI applications with speed, reliability, operational discipline, and visibility from day one.

As AI moves from experimentation to mission-critical infrastructure, organizations face two persistent challenges: how to build AI applications quickly and how to operate them responsibly at scale. Many teams begin by wiring model APIs directly into products, only to encounter unpredictable costs, inconsistent guardrails, provider lock-in, and limited visibility into performance and failures.

Despite rapid adoption, industry research suggests more than 70% of enterprises report challenges moving AI workloads from experimentation into production, citing a lack of foundational infrastructure as a primary barrier. Industry research also estimates that as many as 85% of AI projects fail to move beyond the pilot stage due to operational complexity, governance concerns, and integration challenges.

At the same time, enterprise spending on generative AI infrastructure is projected to exceed $140 billion annually within the next few years, increasing pressure on organizations to manage reliability, cost, and vendor complexity. As AI deployments expand across teams and applications, the need for a unified operational layer has become increasingly urgent. Many enterprises now also operate across multiple AI model providers simultaneously to balance cost, performance, and reliability, further increasing operational complexity.

1-i.ai addresses this gap by introducing a control plane between applications and model providers, allowing teams to build AI features quickly, consistently, and at scale – while operating them with the discipline expected of production infrastructure, all while remaining provider-agnostic.

Organizations interested in participating in enterprise design partnerships or requesting a platform demonstration can learn more at https://1-i.ai.

“AI is now embedded in almost all core products and workflows,” said Deepesh Desai, Founder of One Intelligence. “But most teams are still stitching together glue code around model APIs and building individual applications. We built 1-i.ai to accelerate AI application development while introducing the operational rigor enterprises expect from infrastructure.”

A Unified Platform for Building and Operating Production AI Applications

The platform enables teams to:

– Design and execute deterministic, versioned workflows
– Execute fan-out and fan-in orchestration across multiple providers and strategies
– Route dynamically across multiple model providers
– Publish governed AI applications with stable input/output contracts
– Connect existing applications, services, and tools through a unified ingress contract
– Deploy chat experiences with threaded sessions and memory injection
– Enforce policy and guardrails throughout execution
– Monitor cost, latency, and reliability across applications and providers
– Capture end-user feedback signals tied to requests and applications.

Product, engineering, platform, and operations teams can visually design workflows and publish them as production-ready experiences, including Ingress Apps, Chat Runners, and Memory-Aware Interface, complete with schema validation, authentication, and version pinning.

This approach allows organizations to ship AI applications and features without rebuilding foundational AI infrastructure – orchestration, routing, governance, and observability from scratch.

Built for AI at Scale:
The control plane captures replayable run artifacts for every request, including routing decisions and policy evaluations. This enables deterministic debugging, audit trails, incident investigations, and performance regression analysis.

The platform also includes strategy-based routing, allowing organizations to optimize for cost, latency, reliability, or provider health while avoiding vendor lock-in. All this with end-to-end operational visibility built in through a full observability stack, including metrics, tracing, end-user feedback signals, and dashboards providing real-time insight into performance and cost across applications.

From Experimentation to Infrastructure:
By combining velocity with governance and operational controls in a single operating layer, 1-i.ai helps enterprises reduce time-to-market for AI applications and product features while maintaining operational control.

“We believe AI should run like infrastructure – reliable, measurable, secure, and designed to scale,” Desai added. “But teams shouldn’t have to build that infrastructure themselves. It should be ready to adopt for everyone.”

The 1-i.ai AI Control Plane is now available for enterprise design partners and early production AI deployments.

For more information or to request a demo, visit https://1-i.ai

Deepesh Desai
One Intelligence
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