Seqera is a platform designed for creating, managing, and monitoring computational workflows in scientific data analysis. By integrating with Relevance AI, you can elevate your workflows with advanced automation and AI-driven insights.
Seqera provides a robust platform for managing computational workflows, while Relevance AI empowers these workflows with intelligent automation and AI Agents that can adapt and optimize processes dynamically.
Workflow Orchestration Mastery
AI agent gains advanced capabilities to design, optimize, and automate complex scientific workflows across multiple computing environments.
Cross-Cloud Resource Intelligence
Agent dynamically orchestrates workload distribution across various cloud providers, optimizing for cost, performance, and compliance requirements.
Predictive Resource Allocation
Leverages historical data to anticipate computing needs and proactively adjust resource allocation for optimal performance.
Relevance AI integrates seamlessly with Seqera to enhance your scientific data analysis 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 Seqera account
- A Relevance AI account with access to your project and datasets
- Authorization credentials (you'll connect securely using API keys—no sensitive info stored manually)
Security & Reliability
The Seqera & Relevance AI integration streamlines scientific data analysis by automating workflow management and computational processes. This integration utilizes secure OAuth authentication, ensuring that only authorized workflows can access your Seqera resources. Relevance AI manages API operations (such as creating compute environments, pipelines, and actions) in the background, allowing you to focus on your data analysis without worrying about errors, formatting, or limits.
With built-in validation and type conversion, your workflows can run seamlessly, even when dealing with varying data formats. The integration provides a centralized platform for managing credentials and simplifies the setup of compute environments, making it easier to launch and monitor your scientific workflows.
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.
To get the most out of the Seqera + Relevance AI integration without writing code:
- Start with a well-defined compute environment: Ensure your compute environment configurations are accurate and match platform requirements.
- Use meaningful names: Name your pipelines and actions descriptively to make them easily identifiable.
- Test your workflows: Validate your pipeline and action configurations with test data before deploying them in production.
- Implement error handling: Always check API responses for errors and handle them appropriately to avoid disruptions.
- Monitor execution status: Regularly check the status of your pipelines to ensure they are running smoothly and address any issues promptly.
