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ARRM is a deterministic CI release gate for AI agents. It compares baseline and candidate releases, detects economically harmful regressions in measurable outcomes such as success, cost and latency, and returns a clear PASS, REVIEW or BLOCK decision before deployment. No LLM in the decision path.
Hi Product Hunt 👋
I’m Antonio Orlando, founder of ZEODEC.
We built ARRM around a narrow problem in AI-agent development: a new release can still work technically while quietly becoming worse economically.
Success rate can fall. Cost per successful task can rise. Latency can increase. A business-critical outcome can regress — while the conventional test suite still passes.
ARRM compares a baseline release with a candidate and turns measurable outcomes into a deterministic release decision:
PASS — proceed
REVIEW — investigate before release
BLOCK — economically harmful regression detected
ARRM is deliberately not another general-purpose AI evaluation framework. There is no LLM in the decision path and no subjective judge.
We’re opening a 14-day Early Access trial and looking for teams willing to run ARRM against one real baseline/candidate agent release.
The question I’d most like Product Hunt users to help us answer is:
Would ARRM have stopped a real regression that your existing tests or eval stack would have allowed through?
Thanks for taking a look.
Antonio
Founder, ZEODEC
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About ARRM on Product Hunt
“Catch costly AI agent regressions before release”
ARRM was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #39 on the daily leaderboard. ARRM is a deterministic CI release gate for AI agents. It compares baseline and candidate releases, detects economically harmful regressions in measurable outcomes such as success, cost and latency, and returns a clear PASS, REVIEW or BLOCK decision before deployment. No LLM in the decision path.
ARRM was featured in Developer Tools (518.5k followers) and Artificial Intelligence (477.4k followers) on Product Hunt. Together, these topics include over 199.5k products, making this a competitive space to launch in.
Who hunted ARRM?
ARRM was hunted by Antonio Orlando . 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.
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Antonio Orlando