This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Aural
Open-source AI interviews over voice, chat, and video
Aural is now open source under the MIT license. Design adaptive interviews, share a link, and let Aural conduct the conversation over voice, chat, or video, ask contextual follow-ups, and generate structured reports. Run the managed service or self-host the full Next.js, Supabase/PostgreSQL platform with Docker and pluggable LLM providers.
I built Aural because static question banks and chatbots do not reproduce the rhythm or pressure of a real interview. The hardest parts were real-time voice latency, transcript cleanup, and making follow-up questions feel contextual rather than scripted. This launch opens the complete platform under the MIT license, including voice, chat, video, coding and whiteboard rounds, structured scoring, reports, and candidate practice. I’d especially appreciate feedback on the self-hosting experience and the privacy boundaries teams expect around interview data. Source: https://github.com/1146345502/au...
Tried it on a few mock interviews and the transcript accuracy was better than I expected, especially with multiple speakers. The analytics dashboard made it easy to compare candidates side by side without digging through recordings.
About Aural on Product Hunt
“Open-source AI interviews over voice, chat, and video”
Aural was submitted on Product Hunt and earned 0 upvotes and 2 comments, placing #42 on the daily leaderboard. Aural is now open source under the MIT license. Design adaptive interviews, share a link, and let Aural conduct the conversation over voice, chat, or video, ask contextual follow-ups, and generate structured reports. Run the managed service or self-host the full Next.js, Supabase/PostgreSQL platform with Docker and pluggable LLM providers.
Aural was featured in Android (57.4k followers), Open Source (68.6k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 82k products, making this a competitive space to launch in.
Who hunted Aural?
Aural was hunted by Qingyuan Yang. 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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Qingyuan Yang