Summary
Voker launched an agent analytics product designed to turn AI-agent interactions into structured performance, reliability, and usage data. The product positions observability as a first-class layer for AI product teams rather than a bolt-on dashboard after deployment.
What changed
Voker publicly launched an analytics and observability product for AI agents.
Why it matters
Agent teams increasingly need to measure failure modes, latency, usage patterns, and outcome quality after launch. Voker matters because it treats agent analytics as its own product category, which suggests the market is maturing beyond simple logging and toward purpose-built operating metrics for agents.
Evidence excerpt
Voker describes itself as analytics for AI agents and shows an SDK-driven workflow for instrumenting events, monitoring interactions, and turning agent behavior into team-usable analytics.