Automate AI agent quality testing. Score correctness, detect hallucinations against ground truth, verify policy adherence, and benchmark RAG before bad responses reach real customers.
Hey Product Hunt! 👋
I’m thrilled to share QAgent with you today.
Here’s a dirty secret of modern AI engineering:
We write 50 unit tests for a 20-line backend function. But when we ship a non-deterministic AI agent handling real customers, our "testing pipeline" is typing 3 prompts into the OpenAI playground, seeing it respond politely, and hitting deploy.
The problem? Prompt regression is silent. You tweak one sentence in your system prompt to fix edge case A, and it silently breaks 3 other working customer flows without throwing a single runtime error.
Existing eval tools forced us to write 300 lines of custom Python scripts, pip install heavy libraries, and sift through terminal JSON dumps. We had to maintain an entire second Python codebase just to test our first one!
We built QAgent (https://qagent.in) to fix this for solo builders and agile teams:
⚡ 2-minute setup: Connect your agent via webhook or API endpoint. Zero SDK boilerplate.
🎯 8-dimension evaluation: Answer Quality, Factual Groundedness, Policy Adherence, Escalation Correctness, RAG Faithfulness, Contextual Relevancy, Context Recall, and Multi-turn Context Memory.
🛡️ Zero Python test scripts: Automated parallel test runs with visual pass/fail scorecards and root-cause failure breakdowns.
We’re offering 100 free evaluations every month (no credit card required) so every builder can stress-test their agent before shipping to customers.
I’d love to hear your thoughts, answer any questions, and get your most brutal feedback! 🚀
I built QAgent after watching my own AI agents pass every single playground test, only to break in front of real customers.
The harsh reality of building LLM agents is that single-turn benchmark scores do not translate to multi-turn reliability. If your agent is 95% accurate per turn, the compounding failure rate means it has barely a 35% chance of finishing a 20-turn conversation without hallucinating or breaking rules.
Most solo developers cannot afford to write 200 lines of brittle Python evaluation scripts every time they tweak a system prompt.
QAgent is a zero-bloat automated QA and regression testing platform. You connect your agent through a simple webhook in two minutes without installing any SDK. You can run automated test suites across factual groundedness, policy compliance, RAG faithfulness, and multi-turn context retention, and get a clear 0-100 quality scorecard showing the exact turn where your bot drifted.
There is a free tier with 100 evals every month with no credit card required so any builder can test their bots today.
I would love to hear your feedback, questions, or feature requests!
QAgent
QAgent
Hey Product Hunt! 👋
I am Abhiram, the creator of QAgent.
I built QAgent after watching my own AI agents pass every single playground test, only to break in front of real customers.
The harsh reality of building LLM agents is that single-turn benchmark scores do not translate to multi-turn reliability. If your agent is 95% accurate per turn, the compounding failure rate means it has barely a 35% chance of finishing a 20-turn conversation without hallucinating or breaking rules.
Most solo developers cannot afford to write 200 lines of brittle Python evaluation scripts every time they tweak a system prompt.
QAgent is a zero-bloat automated QA and regression testing platform. You connect your agent through a simple webhook in two minutes without installing any SDK. You can run automated test suites across factual groundedness, policy compliance, RAG faithfulness, and multi-turn context retention, and get a clear 0-100 quality scorecard showing the exact turn where your bot drifted.
There is a free tier with 100 evals every month with no credit card required so any builder can test their bots today.
I would love to hear your feedback, questions, or feature requests!