Automated QA for AI agents. Stop shipping on vibes.
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! 🚀
About QAgent on Product Hunt
“Automated QA for AI agents. Stop shipping on vibes.”
QAgent launched on Product Hunt on September 17th, 2026 and earned 80 upvotes and 6 comments, placing #20 on the daily leaderboard. Automate AI agent quality testing. Score correctness, detect hallucinations against ground truth, verify policy adherence, and benchmark RAG before bad responses reach real customers.
On the analytics side, QAgent competes within Developer Tools, Artificial Intelligence and Bots — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how QAgent performed against the three products that launched closest to it on the same day.
Who hunted QAgent?
QAgent was hunted by Abhiram Reddy.K. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of QAgent including community comment highlights and product details, visit the product overview.
Abhiram Reddy.K