Qabit
Add human eval to any AI app in one line of code
Qabit launched on June 29, 2026 with 10 votes, #1,316 of 22,647 launches that month and more than 90% of that year's launches.
What it does
Qabit adds human eval to any AI app in one line of code. Drop in one script tag. Your team or your users rate every AI response. You get clear, structured feedback you can trust, not guesses. It works with any AI and comes with six ready to use templates (chatbot, RAG, agent, and more). All ratings land in one dashboard so you can track quality over time. It also captures bug reports and product feedback. Free for your first 100 users. Stop guessing if your AI is good. Start measuring it.
Add a structured rating form to any AI product with one script tag. Rate every AI response. Track quality over time. 100 entries/day, free.
Your app uses AI. Qabit lets you rate every response — structured, repeatable, the same way every time. One script tag. That's it. Your AI ships. Responses go out. Users react. But nobody measured if the output was actually good. No rubric. No record. No way to improve. Bad responses reach users with no record. Nobody catches the problem until it's too late. Most teams test code, not AI output quality. No standard way to measure "is this actually good?" You pick one. Nobody has a simple way to combine both in the same workflow. Drop a rating form into any AI product. Collect structured feedback on every response. Works for chatbots, agents, RAG, writing tools, recommendations — any AI…from eval.qa
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QA.tech 1.02025 · qa.tech · ▲413Hi, I'm Daniel, CEO of QA.tech. We've spent the past 18 months developing a cool tool that allows you to run end-to-end tests on any web application using natural language. Check it out and let us know what you think! I used to be a CTO at a B2C marketplace and was taken aback that all qa agencies we talked to wanted to create a custom suite of tests from scratch. Even though we were essentially a e-com with the same functionality as everyone else. Why weren't there any best practices? Some time later my co-founders and I had moved on and were looking for the next thing to do. AI agents…


Quell's UAT AI Agent Platform2025 · quellit.ai · ▲90After years of frustration dealing with slow, costly, and error-prone manual User Acceptance Testing (UAT) at fintechs, I built Quell—-a platform that auto-generates and executes UAT test cases using cross-functional AI experts (e.g. compliance, UX, operations, QA). Quell integrates seamlessly into workflows (Jira, Linear, GitHub), cuts down manual UAT process time by ~80%. I’m excited to get your feedback and answer any questions. Try it free here: quellit.ai Alex [email protected]
We built an AI to review your pull requests2025 · infinitcode.ai · ▲53Hey HN, We’re two developers (co-founders) with a team of 20 who got tired of spending hours reviewing PRs, so we built Infinitcode.ai, an AI-powered code reviewer that: - *Summarizes PRs in plain English*: No more deciphering 1,000-line diff jungles - *Catches more than bugs*: Security holes, performance pitfalls, code smells, even typos (yes, we’ll flag “vurnerabilities” and vulnerabilities) - *Zero onboarding*: Works instantly—no “let me learn your codebase for weeks” nonsense. Why we’re posting: We’re in alpha and need brutal honesty. Roast our tool, mock our UI, or tell us why AI will…
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