Company

19 January 2026

Optimizing AI Energy Costs: Introducing Grid-Aware MLOps with Pado AI

How can you cut AI infrastructure costs while boosting energy efficiency? Discover how VESSL AI and Pado AI are building the industry's first "Grid-aware MLOps." Learn how we optimize workloads based on real-time energy prices and grid status.

Optimizing AI Energy Costs: Introducing Grid-Aware MLOps with Pado AI

As AI workloads scale, so do the challenges of managing operational costs and energy consumption. For infrastructure teams, "efficiency" isn't just about speed anymore—it's about energy intelligence.

We are thrilled to announce our strategic partnership with Pado AI (backed by LG NOVA), a pioneer in data center energy orchestration, to tackle this very challenge.

  • Why Pado AI? Power grid conditions, energy prices, and renewable availability fluctuate constantly. Pado AI specializes in analyzing these signals to determine when and where compute tasks should happen for maximum efficiency.

Building "Grid-aware MLOps" By combining Pado AI’s energy insights with VESSL AI’s orchestration engine, we are developing the industry's first Grid-aware MLOps solution.

Here is how it works:

  1. Insight: Pado AI identifies optimal windows where energy is cheaper or greener.
  2. Action: VESSL AI automatically schedules, migrates, or resumes workloads across global regions and hybrid clouds based on these real-time signals.

The Impact for You


For our users, this means significant reductions in OpEx without sacrificing performance. It allows enterprises to leverage arbitrage in power pricing and commit to sustainable AI practices by prioritizing low-carbon energy sources.

We believe the future of AI infrastructure is not just fast, but smart and sustainable. We are excited to build this future with Pado AI.

👉

Wayne Kim

Wayne Kim

Product Marketer

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