Langfuse is a powerful tool for LLM observability, tracing, and feedback management, allowing you to enhance your AI workflows. With Relevance AI, you can leverage these insights to drive intelligent decision-making and improve your AI applications.
Langfuse provides deep insights into LLM interactions and performance. Relevance AI amplifies these capabilities by enabling intelligent AI Agents to monitor, evaluate, and optimize your applications effectively.
Performance Mastery
Real-time monitoring and analytics provide deep insights into agent behavior and effectiveness
Quality Assurance
Automated evaluation and scoring of responses ensures consistent high-quality outputs
Rapid Troubleshooting
Comprehensive logging and debugging tools enable swift issue identification and resolution
Relevance AI integrates seamlessly with Langfuse to enhance your AI workflows with advanced observability and feedback management.
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 Langfuse account
- A Relevance AI account with API access
- Authorization credentials from both platforms (API keys will be required for secure connection)
Security & Reliability
The Langfuse integration with Relevance AI utilizes secure OAuth authentication, ensuring that only authorized workflows can access your LLM data. Relevance AI manages API operations (such as POST for logging traces and adding feedback) seamlessly in the background, allowing you to focus on enhancing your AI applications without worrying about errors, formatting, or limits.
With built-in validation and structured feedback management, this integration guarantees that your workflows operate efficiently, even when dealing with varying data formats. You can easily monitor and improve your LLM applications while leveraging the powerful orchestration capabilities of Relevance AI.
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 Langfuse + Relevance AI integration without writing code:
- Start with clear trace configurations: Ensure that your trace data includes all required fields and follows a consistent format.
- Utilize structured feedback: Collect feedback using the provided markdown support to enhance clarity and usability.
- Monitor API responses: Implement logging for all API calls to track success rates and response times effectively.
- Validate inputs: Always check that your input data is valid and adheres to the expected formats before sending requests.
- Handle errors gracefully: Use try-catch blocks to manage exceptions and log errors for troubleshooting.
