QALens turns failed checks into smarter checklists. Drop a PR, screenshot, or voice note → get a structured QA checklist with priorities and risk markers. When a check fails, AI expands that one issue into 4-5 related checks for your project — and remembers them. Built for QA engineers and dev teams who want their tools to learn from real bugs, not just generate text. Three inputs, one structured output, project memory built in. Launching late May 2026.

AppSignal — Full-stack monitoring for errors, metrics, and logs

Full-stack monitoring for errors, metrics, and logs

Hey 👋

I've been building QA tools since 2019 — QAProvider for crowd-testing, API testing, performance testing, free checklist managers. Watched QA engineers fight the same problem for years: hours spent on mechanical, repetitive checklist work.

Now AI is finally good enough to do it properly. So I'm building QALens.

But here's what makes it different from "ask ChatGPT to write a checklist":

When a check fails — say, a tester finds a brand name bug on the OAuth screen — QALens turns that one failure into 4-5 related checks (button labels, redirect URIs, consent screens). They stay with your project. Every future checklist for that project remembers.

ChatGPT generates and forgets. QALens generates and learns.

Drop a PR, screenshot, or voice note. Get a structured checklist. Watch it get smarter as you use it.

Launching late May 2026. Early access at qalens.ai — would love your feedback as I build this in public.

— Maxim