AI Response Evaluation Using OpenAI & RAGAS

Say goodbye to untrustworthy AI explanations!

This automation evaluates long-form, conversational agent responses by comparing them to known ground truths — using classification and similarity scoring to measure accuracy and depth. Ideal for agents designed to educate, explain, or guide with nuance.

Whether you’re building support bots, knowledge assistants, or AI tutors, this tool helps ensure your answers are informative, correct, and complete.

What it does:

🧠 Classifies answer content into True Positives, False Positives, and False Negatives
🔍 Compares the agent’s answer to multiple ground truth statements
📊 Calculates an average similarity score across all ground truths
⚖️ Combines classification accuracy and similarity score for a final evaluation
📁 Logs detailed results to Google Sheets for transparent performance tracking

✅ Setup guide & sample scoring sheet included

Need help setting it up? We offer full evaluation design, prompt refinement, and accuracy optimization tailored to your AI use case.