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Result validation is a built-in quality control feature in elvex flows that acts as a supervisor to ensure each step completes successfully before proceeding to the next step.
What is Result Validation?
Result validation is a background supervisor system that automatically checks whether each step in your flow is working correctly and producing valid outputs. The validator is enabled by default for every step you create in a flow.
Think of the validator as a quality control manager that reviews each step's output and determines whether it meets the expected criteria before allowing the flow to continue.
How Result Validation Works
When a step runs in your flow, the validation system:
Analyzes the step's output - Reviews what the step produced
Checks for completion - Ensures the step finished its intended task
Validates quality - Determines if the output meets expected standards
Makes a decision - Either approves the step to continue or flags it as failed
If validation passes, the flow moves on to the next step. If validation fails, the entire flow stops at that point.
When to Use Result Validation
Keep Validation Enabled When:
Accuracy is critical - When incorrect outputs could cause significant problems downstream
Complex processing - When steps involve complex analysis or data transformation
Multi-step dependencies - When later steps rely heavily on the accuracy of earlier steps
Production workflows - When flows are used for important business processes
Consider Disabling Validation When:
Partial results are acceptable - When you'd rather get some output than none at all
Testing and debugging - When you want to see what a step produces even if it's not perfect
Non-critical steps - When a step's failure shouldn't stop the entire flow
Iterative development - When you're still refining your flow and expect some failures
How to Configure Result Validation
Open your flow in the flow builder
Click on the step you want to configure
Look for the validation setting in the step configuration panel
Toggle the "Result Validation" checkbox to enable or disable it
Troubleshooting Validation Issues
If your flow stops due to validation failure:
Check the step's output - Look at what the step actually produced
Review the "Thinking" tab - Examine the AI's reasoning process
Analyze the instructions - Ensure your step instructions are clear and achievable
Consider the input data - Verify that the step received appropriate input
Refine your prompts - Adjust instructions to be more specific or handle edge cases
Impact on Performance and Costs
Result validation does use additional tokens, but this cost is typically offset by preventing wasted processing on subsequent steps with bad input, reducing manual review time, and improving overall flow reliability.