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What is Cumulus Labs?

Cumulus Labs is an intelligent orchestration layer that sits above GPU infrastructure. We aggregate GPUs from major cloud providers and individual data centers worldwide, automatically optimizing your inference workloads so you only pay for the compute you actually use.

Core Value Proposition​

  • Single API, Global Access: Deploy once. Cumulus automatically routes to the best available GPU in the region closest to your users.
  • Pay Only for What You Use: No more renting entire GPUs you don't fully utilize. Our fractional GPU optimization bins small models together, dramatically reducing costs.
  • Eliminate Cold Starts: Through predictive scheduling and intelligent caching, we ensure your models are ready to serve instantly, even during traffic spikes.

Who It's For​

Developers and teams building inference-heavy applications—from security AI agents running multiple specialized models, to RAG systems, to real-time detection pipelines. If you care about latency and want to avoid GPU over-provisioning, Cumulus is for you.

How It Works​

The Aggregation Layer​

Cumulus doesn't own infrastructure. Instead, we aggregate GPUs from:

  • Major cloud providers (AWS, GCP, Azure)
  • Individual data centers and providers globally

This gives us unmatched geographic flexibility and pricing power.

Multi-Cloud + Regional Distribution​

Our platform maintains providers in every major region and country. This means:

  • Geographic Proximity: Your inference runs on GPUs physically close to your users, minimizing latency
  • Regulatory Compliance: Deploy models in specific regions (Switzerland, Saudi Arabia, etc.) without compromise
  • Redundancy: If one provider is overloaded, we route to another instantly

The Optimization Layer Philosophy​

Instead of forcing you to pick specific GPUs or manage infrastructure, you tell us:

  • Which model to deploy
  • What type of workload (inference or training)

We handle the rest: memory estimation, GPU selection, regional routing, fractional allocation, predictive scaling.

Your job is to build the AI. Our job is to run it efficiently.