A customer emails in. An engineer digs through traces for four hours to find the answer.
This is the standard. Slow, manual, and always reveals the problem is bigger than the one complaint that triggered it. The root issue isn't bad engineering - the real problem is a measurement gap. Agent Analytics fills it.
Why Agent Analytics?
How does analytics fit into my observability stack?
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Discover Smart Skills
What does a good Agent Analytics platform actually do?
It fixes your agent!
Voker generates skills for your agent based on user correction data and error logs. Hand them off to your agent, evolving into smarter and smarter versions over time.
What happens if you don't have Agent Analytics?
Failures accummulate silently
Churn goes undiagnosed
Delayed agent improvements
Voker gives you insights into Agent Performance,
surfacing issues before it's too late
surfacing issues before it's too late
Who needs Agent Analytics?
Leadership
"Is our AI agent investment paying off?"
Product
"How are our users' needs shifting over time?"
Engineering
"Where is the system breaking, how do we fix it?"
Data Science
"What behavioral patterns are driving performance?"
Voker is made for the whole team
We provide advanced metrics on Agent Cost Optimization, enabling Leadership to calculate ROI for each agent.
We build behavioral profiles, displaying valuable User Insights to help steer the roadmap for Product and Engineering.
View Auto Annotations
Save time on writing evals!
Voker annotates messages within a conversation, helping you understand both agents and their users.
INTENTS
What are users trying to accomplish
CORRECTIONS
When users push back because the agent did not deliver
RESOLUTIONS
Whether the agent successfully resolved users' requests
Should you build or buy Agent Analytics?
The build instinct is understandable. Agent data feels specific to your product.
The honest accounting: intent detection and resolution tracking is a real data engineering project. LLM APIs change constantly. Keeping accuracy high over time is ongoing work for multiple people - before warehouse integration, versioning, and keeping it running as your agent evolves.
You don't build your own web analytics. You don't build your own product analytics. The argument for building your own Agent Analytics usually sounds better in the planning doc than it does six months into the maintenance burden.
Voker is the Agent Analytics platform purpose-built for the agentic era - intent, correction, and resolution detection out of the box, conversation reconstruction, agent versioning, and direct connections to your data warehouse and product event stream.
The honest accounting: intent detection and resolution tracking is a real data engineering project. LLM APIs change constantly. Keeping accuracy high over time is ongoing work for multiple people - before warehouse integration, versioning, and keeping it running as your agent evolves.
You don't build your own web analytics. You don't build your own product analytics. The argument for building your own Agent Analytics usually sounds better in the planning doc than it does six months into the maintenance burden.
Voker is the Agent Analytics platform purpose-built for the agentic era - intent, correction, and resolution detection out of the box, conversation reconstruction, agent versioning, and direct connections to your data warehouse and product event stream.
FAQ
How does Voker differ from traditional logging and tracing tools?
Is there a free version of Voker?
How quickly can we integrate Voker?
Which AI providers and frameworks does Voker support?
Do we need a data science team or engineers to use Voker effectively?
What business outcomes can we expect from Voker?