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VokerSupport & Serve Customers

STOA rating

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What it does

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Voker helps you see exactly how your AI agents (automated software that handles conversations with users) are performing — so you can fix problems before customers leave. You get dashboards that track whether your agent understood users, made mistakes, and actually solved their problems. No engineering ticket required to pull insights.

Strengths

Self-serve analytics so non-engineers can pull insights without filing tickets
Tracks three specific metrics — intents, corrections, and resolutions — that directly show agent quality
Designed for teams handling 1,000+ chat sessions per month, so it scales with growth
Connects conversational data to business outcomes like churn and conversion

Weaknesses

Positioned for teams already running AI agents at scale — not useful if you haven't deployed an agent yet
No public pricing details found, making it hard to budget before signing up
Early-stage product with limited public proof of traction or customer case studies

Key features

Track intent classification (what users are trying to do) across every conversation automatically
Detect correction events — moments when users had to repeat or fix something the agent got wrong
Measure resolution rates to see how often your agent actually solves user problems
Give product and business teams self-serve access to agent performance data
Connect agent metrics to business outcomes like retention and conversion

AI features

Voker uses AI to automatically classify user intents, detect correction events, and measure resolution rates across agent conversations.

STOA verdict

Voker is built for small-to-mid-size tech teams that have already deployed AI chat agents and need to measure whether those agents are actually working. If you're running a customer-facing AI agent and flying blind on performance, this fills a real gap. That said, pricing isn't public and the product appears early-stage, so budget carefully and ask for a demo before committing.