Introducing The Latest Release of RAVEL Orchestrate AI - Smarter, Faster Infrastructure Decisions Continuously
AI infrastructure is evolving quickly — and with that comes a new level of operational complexity.
Teams are no longer managing isolated GPU clusters or single-site environments. They’re operating distributed AI platforms across sites, tenants, compute environments, and increasingly dynamic workloads, all while balancing performance, cost, energy efficiency, governance, and scale.
Orchestrate AI was built for this shift.
Policy Manager: The Intelligence Layer Behind Orchestrate AI
At the center of the release is the new Policy Manager — the intelligence layer behind Orchestrate AI. Designed as a real-time operational control plane for AI infrastructure, Policy Manager helps organizations make smarter, faster infrastructure decisions continuously.
Policy Manager evaluates available compute targets using live telemetry, workload requirements, cost models, energy intelligence, network conditions, and operational policies to determine the best placement for every AI workload.
The result is infrastructure that operates more intelligently — with greater efficiency, visibility, and control.
Ready to see Policy Manager in action? Talk to our team.
With the latest release, teams can:
- Optimize GPU utilisation across distributed environments
- Balance performance, cost, and power consumption dynamically
- Introduce policy-driven governance for AI workloads
- Automate infrastructure decisions with human oversight
- Improve sustainability outcomes through energy-aware scheduling
- Gain deep operational visibility through analytics and audit tooling
The result is infrastructure that runs smarter. Not just harder.
Policy Manager: Human-in-the-loop Workflow
Policy Manager also introduces Pending Actions — a human-in-the-loop workflow system that enables operators to review, approve, modify, or automate optimization recommendations such as rebalancing, quota enforcement, preemption, and node preparation.
Policy Manager: Workload Aware Scheduling
Alongside this, Workload Profiles allow organizations to define workload-aware scheduling behaviors based on latency requirements, infrastructure compatibility, precision support, migration policies, and sustainability priorities.
Orchestrate AI marks a shift from static infrastructure management to intelligent, policy-driven AI orchestration — built for the scale, complexity, and operational realities of enterprise AI.
This is orchestration designed for the next generation of AI operations.