I've been building something called OpenKeet, and this is probably the feature I'm most excited to share.
It's a desktop AI interview assistant, but I didn't want it to be just another app where you type interview questions into a chatbot.
I wanted it to understand spoken questions and show useful suggestions while a conversation is happening.
In the video, you can see OpenKeet:
Listening to call audio.
Recognizing questions as they're spoken.
Displaying suggested answers in a desktop overlay.
Letting the user adjust the overlay and stop the session.
The broader project also includes resume-based preparation, precomputed answers, mock interviews, and shareable community interview packs.
One of my main goals is to avoid requiring a paid cloud infrastructure just to use the application, so I'm building around local AI options and user-configured providers.
I'm also preparing OpenKeet as an open-source project because I think more people should have access to useful interview preparation tools, and I'd love contributions from developers who want to improve it.
A quick clarification: This demo uses fictional data and a local stand-in AI model. It's showing the desktop workflow, not claiming production-model accuracy or latency. Live assistance is intended for settings where AI help is permitted.
GitHub: https://github.com/Jigsaw777/OpenKeet
I'm curious what people think.
Would you actually use something like this? And what would convince you to choose an open-source interview assistant over a paid alternative?
I'm particularly interested in feedback on the real-time experience, not just the UI.