RYAX is an open-source hybrid IT workflow orchestrator that enables efficient management of AI resources across edge, cloud, and high-performance computing environments. By utilizing serverless GPU/CPU/RAM and GPU fractioning technologies, it optimizes resource usage and reduces costs while providing observability and intelligent orchestration for AI workflows.
Funding
$1.4M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Managing AI workloads across diverse infrastructure (edge, cloud, HPC) is complex and resource-intensive, leading to inefficient resource utilization and increased costs. Existing solutions often lack the flexibility to adapt to varying workload demands and fail to provide adequate observability across hybrid environments.
Solution
RYAX is an open-source hybrid IT workflow orchestrator designed to optimize the ROI of AI workflows by enabling efficient resource management across edge, cloud, and high-performance computing environments. It leverages serverless GPU/CPU/RAM allocation, GPU fractioning, and bin packing technologies to ensure resources are used only when needed. The platform offers a low-code environment with built-in reusable triggers and actions, along with AI-assisted code generation, to accelerate workflow creation. RYAX intelligently orchestrates actions based on constraints such as data privacy, cost, and power consumption, allowing users to execute workflows where they are most effective.
Target Audience
RYAX targets data scientists, machine learning engineers, and IT professionals responsible for deploying and managing AI workloads across hybrid infrastructure.
Features
- Serverless GPU/CPU/RAM allocation for on-demand resource provisioning
- GPU fractioning to optimize GPU utilization across multiple workloads
- Low-code workflow builder with reusable triggers, actions, and AI code generation
- Intelligent orchestration based on data privacy, cost, and power consumption constraints
- API-first design for seamless integration with internal and external services
- Observability tools for monitoring workflow deployments and executions
- Support for workflow versioning, pausing, stopping, and modification
- Hybrid infrastructure support, including edge, cloud, and HPC environments