GenAI Innovation
Optimise Workflows. Reduce Compute Costs. Access The Hardware You Need.
Source global GPU and CPU capacity, optimise AI workloads, slash costs with Spot compute.
Works With Your Existing Stack
Keep using PyTorch, Ray, Kubernetes, or your existing workflows — YellowDog automatically identifies the target hardware, handles provisioning, scaling and cost optimisation across clouds.
Do more with your workflows
YellowDog keeps every instance fully utilised — pipelines are optimised and workloads complete faster
Match compute needs with maximum performance
✓ Know where capacity is available at what cost
✓ Identify new hardware without the guesswork
✓ Use Spot as a viable training strategy
Orchestrated for end-to-end workflow optimisation
✓ Workflows mapped to available hardware
✓ Multi-cluster orchestration across fleets
✓ Elastic scaling across regions & clouds
Cost efficiency built into every workload
✓ Maximum latency & throughput efficiency
✓ Highest compute node utilisation
✓ No idle compute so no wasted spend
Best Source of Compute
YellowDog continuously analyses availability, performance, and price across clouds to provision the optimal CPU and GPU resources for every workload—maximising utilisation while minimising cost.
GENAI COMPUTE PLAYBOOK
Five Step Plan to Running Workflows on New Hardware
Use our purpose-built playbook to allow any GenAI engineering team to confidently identify, validate, and run production workloads on optimal hardware — faster and cheaper.
We track real-time GPU and CPU availability across every major cloud provider, region, and chipset. Tell us your workload, model size, training frequency, throughput, latency, budget and we surface the best available match on price and performance, including options you might not have considered
YellowDog Insights ranks every candidate by price, performance, and price-performance ratio for your specific workload: training, inference, or agentic. You see the full picture, not just what's popular.
We run your workload on target hardware before you commit a single line of re-engineering. Quality, latency, and throughput confirmed first. Engineering time spent only when confidence is production-grade.
Knowing hardware is cheap in theory is not enough. We confirm real supply availability at production scale across your preferred regions so your engineering investment is protected before a line of code is written.
Hardware validated, capacity confirmed, we build the full cost model and configure Spot across training, inference, and agentic pipelines. Automatic interruption recovery makes Spot production-viable, not just experimental.
GenAI Acceleration Starts With Compute You Can Rely On
Give your engineering teams the freedom to optimise pipelines across different architectures, with full confidence in hardware availability, performance and cost.
Starter
IDEAL FOR START-UPS
✓ Instantly identify target hardware
✓ Real-time CPU / GPU benchmarking
✓ ~100% compute node utlilisation
✓ Intelligent multi-region provisioning
✓ Your workflows onboarded & optimised
✓ End-to-end orchestration with Spot compute
Enterprise
IDEAL FOR SCALE-UPS
✓ Everything in Starter
✓ Unlimited clusters
✓ Pipeline validation support & capacity assurance
✓ Pro level Insights portal
✓ 24×7 dedicated support
✓ Grafana dashboards & custom reporting
How To Get Started
We’ll configure your clusters, onboard your workflow, and give you $500 in compute credit. You just bring the code. No contracts. No upfront costs.
