Building Trust When Everyone Has a Mic

Anyone can say anything, and usually does. Podcasts, livestreams, panels-opinions move fast, and audio moves even faster. Most of it goes unchecked. By the time you think, "Wait, is that actually true?" the conversation is already five minutes ahead.

For a long time, audio has been high friction. It's hard to pause and check a quote, harder to find the source, almost impossible to get the full context in real time. Misinformation loves these gaps. It hides in the space between what's said and what's actually known.

We're trying to make that gap smaller.

The goal isn't to judge what's right or wrong, but to make it almost effortless to pull up the context. If a big claim drops in the middle of a podcast, you should be able to see exactly what was said, plus the references and sources behind it-without waiting for someone on Twitter to call it out two days later.

AI helps with the heavy lifting: transcribing the audio, surfacing the statements, searching for supporting material across the internet. But the important part isn't the answer the AI gives. It's the trail it leaves-the links, the transcripts, the original documents. Everything is visible. If you want, you can dig as deep as you like. If not, the context is there anyway, a layer under the conversation.

We don't need more truth-tellers. We need more context, more receipts, less friction. If people can actually see where a claim comes from and how it connects to the real world, trust becomes something you can build-not something you just hope for.