RAG Engine
Optimize

A/B Testing

Scientifically test different prompts, models, and configurations to maximize AI performance.

The Challenge

Without A/B testing, you're guessing which prompts, models, and settings work best. Small changes can have big impacts, but you can't measure them.

How It Works

1

Create Variants

Set up different versions of prompts, models, or configurations to test.

2

Split Traffic

Automatically route users to different variants based on your testing criteria.

3

Measure & Deploy

Analyze results with statistical significance and deploy winning variants.

Benefits

Data-Driven Decisions

Make optimization decisions based on real user data, not guesswork.

Continuous Improvement

Systematically test and improve your AI's performance over time.

Risk Mitigation

Test changes with a subset of users before rolling out widely.

Statistical Rigor

Built-in statistical analysis ensures results are significant, not random.

Comparison

FeatureRAG EngineChatbaseCustomGPTDify
Prompt A/B Testing
Partial
Model Comparison
Statistical Significance
Automatic Winner Selection
Partial

Based on publicly available feature lists as of 2024

Use Cases

Prompt Engineering

Test different system prompts to find the most effective instructions.

Model Selection

Compare GPT-4 vs Claude vs other models for your specific use case.

Response Optimization

Test different response formats, lengths, and tones with users.

Retrieval Tuning

Optimize chunk sizes, overlap, and retrieval parameters.

Ready to Experience This Feature?

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