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Record ~50 seconds of your engine and EngineEar AI tells you what's likely going on — mechanical causes, urgency, and what to check before the workshop. Wear evaluation: does your engine sound its age? The AI compares its acoustic fingerprint to what a car of your make, year and mileage should sound like. Your garage stays free: multiple vehicles, fuel log, maintenance history, cost stats, backup and restore. Only AI analyses are subscription-based. 21 languages.
Hey Product Hunt,
We built EngineEar AI because we were convinced that engine sounds carry more information than we give them credit for. A motor doesn't just "run" — it exhales its condition through vibration, exhaust rhythm, valve ticks, injector timing. Every one of those is a signal, and modern audio models have quietly become good enough to read them.
The feature we're proudest of is wear evaluation: when the AI listens to your engine, it doesn't just look for individual defects — it compares the overall acoustic signature against what a car of your make, model, year, and mileage should sound like. If a 5-year-old car with 50,000 km already sounds like a 200,000 km workhorse, that's worth knowing. Not as a final diagnosis, but as a data point you can bring to your mechanic so you walk in informed instead of guessing.
Everything else is built around that idea. Guided Mode walks you through 30 s of idle + 50 s of revs so the model gets a clean signal. Free Mode lets you record on your own terms. And the whole vehicle side stays free — multiple profiles, fuel log, maintenance schedule with reminders, cost stats, backup and restore — so the AI actually has your vehicle context to compare against. Only the analyses themselves are on subscription.
One honest thing upfront: recognition quality depends on the microphone. Built-in phone mics roll off the low and high frequencies that carry the most diagnostic signal, and background noise amplifies that gap. Because of that variance across phones and environments, the AI errs on the side of flagging — sometimes calling out findings a mechanic would shrug at. In a quiet spot with a decent external mic clipped near the engine, the assessments get sharp. Straight from your phone in a windy parking lot, treat individual line items with a grain of salt and trust the overall trend.
What we'd love your feedback on:
– Try Guided Mode with your own car and tell us if the diagnosis + wear evaluation feel plausible for what you know is going on under the hood.
– Does the "one-time service events" flag in the garage match how you actually track things like warranty extensions or seasonal tire swaps?
– Anything about the result presentation that reduces your trust — missing confidence indicator, jargon, urgency scale?
Thanks for looking, and for the honest takes.
How accurate is the AI actually for weird noises like timing chain rattle versus a worn tensioner? Would love to see what kind of confidence score it gives before I trust it over my mechanic.
does the ai just guess at what might be wrong or does it actually pull from a database of real engine sound samples for my specific model? curious how confident the diagnoses actually are before i pay for a subscription.
About EngineEar AI on Product Hunt
“Weird engine noise? AI tells you what it is.”
EngineEar AI was submitted on Product Hunt and earned 5 upvotes and 5 comments, placing #133 on the daily leaderboard. Record ~50 seconds of your engine and EngineEar AI tells you what's likely going on — mechanical causes, urgency, and what to check before the workshop. Wear evaluation: does your engine sound its age? The AI compares its acoustic fingerprint to what a car of your make, year and mileage should sound like. Your garage stays free: multiple vehicles, fuel log, maintenance history, cost stats, backup and restore. Only AI analyses are subscription-based. 21 languages.
EngineEar AI was featured in Android (57.3k followers), Cars (6.2k followers) and Artificial Intelligence (473.1k followers) on Product Hunt. Together, these topics include over 151k products, making this a competitive space to launch in.
Who hunted EngineEar AI?
EngineEar AI was hunted by Ali. 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 EngineEar AI stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.