Machines don't just break. They whisper first — weeks before they fail. But standard monitoring samples are too slow to hear them, and cloud AI can't scale across thousands of distributed assets. AIRS ML creates edge AI devices that mount onto any asset — CNC machines, robotic arms, motors, spindles, pumps — and detects incipient faults weeks before failure. Runs entirely on-device at 100 kHz, air-gapped, no cloud required. Validated across assets and John Deere startup collaborator 2026.
Hey Product Hunt 👋 Prateek here, founder of AIRS ML.
This one started with my dad. He spent 30 years in oil & gas reliability, and I grew up watching him take 3 am calls about machines that died without warning. Turns out machines do warn you; they vibrate at frequencies no one was listening to, weeks before they fail.
So we built a small edge AI device that listens. Mounts on any motor, spindle, pump or conveyor. Runs on-device at 100 kHz. No cloud. No labelled failure data needed.
Would love your feedback, especially from anyone who's lost a weekend to a machine that "just died." 🛠️
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About AIRS ML on Product Hunt
“Edge AI that predicts machine failures”
AIRS ML launched on Product Hunt on April 28th, 2026 and earned 78 upvotes and 1 comments, placing #26 on the daily leaderboard. Machines don't just break. They whisper first — weeks before they fail. But standard monitoring samples are too slow to hear them, and cloud AI can't scale across thousands of distributed assets. AIRS ML creates edge AI devices that mount onto any asset — CNC machines, robotic arms, motors, spindles, pumps — and detects incipient faults weeks before failure. Runs entirely on-device at 100 kHz, air-gapped, no cloud required. Validated across assets and John Deere startup collaborator 2026.
AIRS ML was featured in Internet of Things (225.6k followers), Artificial Intelligence (467.3k followers) and Pitch London (2 followers) on Product Hunt. Together, these topics include over 98.6k products, making this a competitive space to launch in.
Who hunted AIRS ML?
AIRS ML was hunted by Rajiv Ayyangar. 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.
Want to see how AIRS ML stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Rajiv Ayyangar
Hey Product Hunt 👋 Prateek here, founder of AIRS ML.
This one started with my dad. He spent 30 years in oil & gas reliability, and I grew up watching him take 3 am calls about machines that died without warning. Turns out machines do warn you; they vibrate at frequencies no one was listening to, weeks before they fail.
So we built a small edge AI device that listens. Mounts on any motor, spindle, pump or conveyor. Runs on-device at 100 kHz. No cloud. No labelled failure data needed.
Would love your feedback, especially from anyone who's lost a weekend to a machine that "just died." 🛠️