Voker

Most AI teams are flying blind with their agents. You ship an agent, it starts chatting with users, and somewhere between the prompt and the response, you have absolutely no idea what's actually happening. Are users getting value? Is the agent hallucinating? Hitting edge cases? You'd need a PhD in trace archaeology to figure it out—and by then, your churn has already told you the story.

That's where Voker comes in. It's the analytics platform specifically built for AI product teams who want to understand what their agents are actually saying to users—not just token counts and latency logs, but actual performance intelligence. Voker lets PMs and business teams self-serve insights without filing tickets and waiting for engineering to pull data. You get conversational analytics, abnormality detection, and knowledge gap identification so you can iterate fast. Plus, they hook agent metrics to business outcomes—conversion, retention, revenue—so you can actually prove AI ROI to stakeholders who speak fluent spreadsheet.

The installation takes about two minutes: copy-paste their AI prompt into your coding tool, it scaffolds the SDK and instruments your first event. Works via pip too if you're old school about it. Currently just launched on Product Hunt, so the early momentum is real. If you're building agents and can't answer basic questions about whether they're helpful or harmful, you basically have a black box in production. Voker wants to change that.