Postcasts have had a discovery problem that’s gone mostly unaddressed for years.
A show can rack up loyal listeners, book brilliant guests, and produce hours of genuine expertise, and almost none of that ends up where people actually look for answers.
Search engines can’t listen. AI assistants can’t press play. The result is that some of the most useful conversations on the internet sit inside audio files that the web’s main discovery systems treat as nearly invisible.
Poddisco, a new product from The Discoverability Company, claims they can close that gap. Founded by Drew Chapin, a Philadelphia-based “startup guy,” poddisco has opened a limited free beta for podcast creators and plans to name its first five participants on July 1st. Creators who want to be considered can apply now at poddisco.com.
Poddisco turns podcast episodes into searchable, indexable, AI-readable web pages. Rather than leaving an episode as an audio file with a short description, the product builds out full transcripts, structured metadata, topic hubs, guest hubs, and schema markup so that traditional search engines and the newer generation of AI answer engines can read, understand, and surface what was actually said.
Chapin frames the underlying issue in terms anyone who has run a show will recognize.
“A podcast is a library of expertise, but most of that value is locked inside audio that search engines can’t read,” he has said. That line captures the thesis behind the product. Each episode is treated less as a media file and more as a body of knowledge that deserves a proper home on the open web, where it can be crawled, cited, and found.
It helps to look at what a podcast usually leaves behind. A typical episode lives on a hosting platform and gets pushed out to the major listening apps. The text that travels with it is often a title, a paragraph of show notes, and maybe a list of timestamps. For a forty-five minute conversation packed with names, claims, recommendations, and stories, that’s a very thin layer of text. When someone types a question into Google or asks an AI assistant for a source, there’s almost nothing for those systems to match against. The conversation might answer the question perfectly, yet it never shows up.
Poddisco widens that text layer dramatically. A full transcript gives search engines real language to index. Topic hubs gather every moment a show touched a given subject over many episodes, which can help a creator rank for the themes they cover most. Guest hubs collect appearances by a particular person, which matters as guest-driven discovery becomes more common. Schema markup, the structured data that tells search engines what a page contains, helps machines interpret all of it correctly. Together, the work is meant to make an episode legible to the systems that decide what gets surfaced.
As more people turn to AI assistants for direct answers rather than scrolling a list of links, the question of whether a source can be read by a machine has grown more urgent. Audio that no model can parse tends to be left out of those answers entirely. By rendering episodes as clean, structured, text-rich pages, Poddisco is trying to give podcasts a fighting chance to be included when an AI system assembles a response. Whether that fully pays off will depend on how the engines evolve, but the direction of travel seems clear enough.
The beta itself is deliberately small. Rather than opening the doors to everyone at once, TDC is selecting a limited group of creators to work with closely, with the first five participants set to be named on July 1st. A constrained cohort is a sensible way to start. It lets the team learn from real shows with real archives, tune the output to what creators care about, and avoid overpromising before the method has been tested on different formats. Interview shows, narrative series, and niche expert podcasts all present different problems, and a focused group should surface those differences quickly.
For creators weighing whether to apply, the math is fairly low-risk during a free beta.
A show that has built up a deep archive of episodes is sitting on a large catalog of content that has never been made fully discoverable. Turning that archive into indexable pages could open a channel of discovery that audio alone has never provided, which is search and AI traffic that finds the show because the words inside it can finally be read.
The bigger bet, the one TDC is making with Poddisco, is that the future of podcast growth won’t come only from app charts and social clips. It will come from being findable wherever people search, AI tools included, since those tools are quietly becoming a front door to the web. If that’s right, making episodes readable isn’t a nice-to-have but a foundation.
Podcast creators interested in the limited free beta can apply at poddisco.com. The first five participants will be named on July 1st.
