Tyto is a lightweight model that runs on your audio stream and predicts whether the audio reaching your agent will cause downstream failures. It outputs a single score plus a breakdown across six dimensions: noise, speaker reverb, speaker loudness, interfering speech, background media speech, packet loss. Try it here: https://ai-coustics-tyto-demo--ph.modal.run/
Hi everyone, I'm Fabian, co-founder at ai-coustics. The launch page covers very well what our newest product does but let me add here why we built it.
Voice agents are moving into the real world, where audio is messy: think cars, call centers, kitchens, noisy streets. And in the real world they fail in ways the transcript never shows. Especially competing voices - like a TV in the background or a far-field speaker - and artifacts like packet loss on a bad connection can throw off agent's performance. Teams see the bad outcome but have no idea the cause was audio. That blind spot is where trust in production voice AI breaks down.
Tyto (Audio Insight) is the solution for that blind spot. It analyses the input audio and scores it: how noisy, how reverberant, how much interfering speech, how likely the agent is to mishear. It's a signal you can actually act on. It works in two modes: real-time monitoring so you catch failing calls as they happen or adjust the agent flow, and post-call analysis so you can finally answer what went wrong. And it runs on the same on-device ai-coustics SDK that's already shipped in production by voice AI teams.
Easiest way to feel it: point Tyto at a recording of one of your worst calls and watch it highlight exactly where the audio fell apart. Full write-up here. Link to documentation here.
We built this for the people shipping voice agents into hard environments. Tell us what's missing, we're reading every comment. 🙌
Any plans to ship this as a small SDK for mobile apps, or is it mainly for web and call center setups?
For anyone who wants to try this hands-on: we’ve open-sourced the demo agent codebase so you can run it yourself or see how to integrate it into your own voice agent setup. Check it out here: [link]
This is a useful blind spot to solve. In sales and support voice agents, transcripts often hide the real reason trust broke down. Do you see Tyto feeding a live confidence/risk signal into the agent policy, like switching to confirmation mode, slowing down, or escalating to a human when audio quality crosses a threshold?
Looks great! Does running on-device add latency to the live call, or is the scoring free?
Congrats on the launch! I'm curious what specific agent flow adjustments can Tyto trigger automatically when it detects interfering speech mid-conversation?
It basically feels like the Voice AI agents are not deaf anymore! I think there was some degree of the Audio Intelligence in some of the STT engines such as understanding certain sounds etc but the acoustics awareness is a whole new level!
Hey hey, Mila from ai-coustics here - I'm looking forward to seeing what you all think!
If you want to try it in your own infrastructure right away, you can get your SDK key here 😊 You can find full docs here: https://docs.ai-coustics.com/
About Tyto by ai-coustics on Product Hunt
“Audio insight that predicts voice AI performance”
Tyto by ai-coustics launched on Product Hunt on June 17th, 2026 and earned 101 upvotes and 17 comments, placing #15 on the daily leaderboard. Tyto is a lightweight model that runs on your audio stream and predicts whether the audio reaching your agent will cause downstream failures. It outputs a single score plus a breakdown across six dimensions: noise, speaker reverb, speaker loudness, interfering speech, background media speech, packet loss. Try it here: https://ai-coustics-tyto-demo--ph.modal.run/
Tyto by ai-coustics was featured in Developer Tools (515.4k followers), Artificial Intelligence (473.1k followers) and Audio (2.1k followers) on Product Hunt. Together, these topics include over 184.2k products, making this a competitive space to launch in.
Who hunted Tyto by ai-coustics?
Tyto by ai-coustics was hunted by Justin Dorber. 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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Justin Dorber
Hi everyone, I'm Fabian, co-founder at ai-coustics.
The launch page covers very well what our newest product does but let me add here why we built it.
Voice agents are moving into the real world, where audio is messy: think cars, call centers, kitchens, noisy streets. And in the real world they fail in ways the transcript never shows. Especially competing voices - like a TV in the background or a far-field speaker - and artifacts like packet loss on a bad connection can throw off agent's performance. Teams see the bad outcome but have no idea the cause was audio. That blind spot is where trust in production voice AI breaks down.
Tyto (Audio Insight) is the solution for that blind spot. It analyses the input audio and scores it: how noisy, how reverberant, how much interfering speech, how likely the agent is to mishear. It's a signal you can actually act on.
It works in two modes: real-time monitoring so you catch failing calls as they happen or adjust the agent flow, and post-call analysis so you can finally answer what went wrong. And it runs on the same on-device ai-coustics SDK that's already shipped in production by voice AI teams.
Easiest way to feel it: point Tyto at a recording of one of your worst calls and watch it highlight exactly where the audio fell apart. Full write-up here. Link to documentation here.
We built this for the people shipping voice agents into hard environments. Tell us what's missing, we're reading every comment. 🙌