RunPod is a cloud platform offering scalable GPU infrastructure for AI and machine learning workloads.
Enhance your AI capabilities with powerful AI Agents that leverage RunPod's computing resources for sophisticated automation and analysis.
RunPod provides scalable GPU computing power for AI workloads. Relevance AI transforms this raw computing potential into intelligent AI Agents that can process, analyze, and act on complex data at scale.
Rapid Deployment
Agents can quickly implement AI models, accelerating time to market.
Cost Efficiency
Utilizing a pay-as-you-go model reduces infrastructure expenses significantly.
Enhanced Performance
Access to powerful GPUs boosts the training and inference capabilities of agents.
Relevance AI gives you access to RunPod's GPU-powered infrastructure and machine learning capabilities within your automated workflows.
What you’ll need
You don't need to be a developer to set up this integration. Follow this simple guide to get started:
- A RunPod account
- A Relevance AI account with API access enabled
- Authorization credentials (secured via API keys—no manual storage required)
Security & Reliability
The integration leverages secure OAuth authentication to safely access your RunPod resources and endpoints. Relevance AI manages API operations seamlessly in the background, handling request methods and data transformations automatically.
Built-in validation ensures your workflows execute reliably across RunPod's compute infrastructure and API services.
No training on your data
Your data remains private and is never utilized for model training purposes.
Security first
We never store anything we don’t need to. The inputs or outputs of your tools are never stored.
Best Practices for Non-Technical Users
To get the most out of the RunPod + Relevance AI integration without writing code:
- Configure API endpoints properly: Ensure correct base URL and endpoint paths for RunPod requests.
- Manage authentication: Keep OAuth tokens secure and up-to-date for seamless API access.
- Optimize request payloads: Structure API call bodies efficiently for best performance.
- Handle responses appropriately: Implement proper error handling and response validation.
- Monitor usage: Track API calls and resource consumption to stay within RunPod limits.
