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Checksum is an AI-native continuous testing platform for engineering teams shipping faster than manual QA can keep up. It generates, runs, and auto-heals end-to-end and API tests on every pull request, all as standard Playwright code in your own repo. When a test fails, Checksum tells you whether it found a real bug or a stale test, then fixes the false failures so your suite keeps pace with your coding agents.
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👋 Hey Product Hunt, I'm Gal, founder and CEO of Checksum.
A few years ago at my last startup, I watched our team lose entire sprints to test maintenance. Every time the product changed, someone had to go update selectors, re-triage failures, and figure out which broken tests were real bugs and which were just noise. I'd spent years before that building ML models to detect suspicious activity from satellite data—pattern recognition at scale—and it nagged me that software testing was the same kind of problem.
AI coding tools solved generation and teams can now ship far more code than ever. But they didn't solve verification; every PR still needs to be tested and trusted before it ships. Counterpart, an agentic insurance platform, runs a 10x QA team on Checksum at less than half the cost of one offshore developer, and hasn't had a production outage since. Their engineering manager Ron Alexssen put it this way: "For less than half the salary cost of an offshore developer, I have the impact of a full QA team."
That’s why we built Checksum. Our agentic loop runs in two parts:
🔁 Generate and maintain. On every pull request, an agent spins up in a sandbox, detects what changed, and generates or updates your End-to-end and API tests automatically. No written selectors by hand.
🔁 Run, report, fix. Trigger your suite from a PR, the API, or MCP. When something fails, a second agent triages it: real bug, or broken test by a product change? Real bugs route to Jira, Linear, or Slack. Broken tests get fixed autonomously. Söderberg & Partners went from zero to full coverage in weeks and now reclaims 90 hours of manual testing a month. Postilize cut bugs by 70% and sped up engineering cycles by 30%, with zero flaky tests.
Everything ships as standard Playwright code committed to your own repo. No proprietary format, no lock-in. And the agent doesn't just chase easy passing tests, it goes after the hard cases too: auth boundaries, edge flows, the stuff that's tedious to test manually and easy for AI to skip if you let it.
🎁 Product Hunt community gets a free 30-day trial with code PHLAUNCH
We're here all day, ask us anything. 🙏
The stale test detection is the part that caught my attention. AI generated code is only useful if the tests dont become another maintenance job.
Checksum AI
@ashir_murtaza1 Yes! Generating tests quickly is the easy part now. The hard part is what happens after that first test when your app's changed multiple times and half your suite is red for reasons that have nothing to do with a real bug.
With Checksum every failure gets triaged before it ever hits you team: real bug vs. stale test. Real bugs route straight to your team. Stale tests get healed. 70% of failures resolve that way without anyone touching them.
If you've been burned by a suite that turned into a maintenance job before, genuinely curious what broke it, selectors, flaky timing, something else? Helps us make sure we're solving the actual pain, not just the version of it we assumed.
Buffup.AI
Playwright code staying in the repo is a nice choice. i do much rather have tests i can inspect and edit than another black-box- QA layer.
Checksum AI
@sansa_grey That's why we went with it. With Playwright in your repo, you can read exactly what a test does, edit it if something's off, and if you ever walk away from Checksum, every test walks with you. No migration, no rewrite.
It also means the tests fit into whatever review process you already trust, a generated test shows up as a normal PR, gets reviewed like any other code change, not approved through some separate tool.
@benln can it test changes across multiple services in the same PR?
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@benln @rosalie_autumn yes it can! Checksum specializes in complex cases across surfaces and users
The take test detection caught my attention. False failures can waste so much time that fixing those automatically could be really useful.
Checksum AI
@athar_jatoi Agreed, and the false failures are often worse than the real ones because they train people to ignore the suite. Telling a real bug from a stale test is the core of what the healing workflow does.
Littlebird
Would you suggest using this for more elaborate claude code projects (full stack, hosted)? I'm the owner of a few of our internal tools and I'm trying to figure out where I can/should fit something like Checksum into the stack. I'm frequently worried about random bugs and keeping the tools running as smoothly as possible.
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@michaelsand Yep, our bread and butter is complex applications
Bababot
I like the idea of keeping everything as normal Playwright tests. makes adopation much easier for an existing engineering team.
Checksum AI
@adams_parker Exactly! Your test is yours whether you stay with Checksum or not.