Skip to main content

Overview

Automated annotations are Voker’s analytics layer for AI agents in production. Every event you send to Voker is automatically labeled with what the user was trying to accomplish, where the agent got something wrong, and whether the user’s intent was fulfilled.

Annotation types

Voker produces three kinds of automated annotations.

Intents

What the user is trying to accomplish.

Corrections

Where the agent got something wrong.

Resolutions

Whether an intent was actually fulfilled.

Categorization

We automatically categorize these annotations into broader Categories. Read more about this process in the Categorizations documentation.

FAQ

Definitely! We are constantly improving our automated annotations system so that it’s immediately helpful out of the box.
Yes. Contact the team to customize how intents, corrections, and resolutions are detected to reflect your product’s reality instead of a generic default.
Every event you send is annotated automatically.
Contact the team to get your exported annotations.
Logs and traces help engineers debug one conversation at a time. Automated annotations tell you what’s happening across all of them — what users are asking, where the agent keeps breaking, and whether agents actually deliver. They close the measurement gap that existing observability and product analytics tools weren’t built for.
No. Evals catch regressions against scenarios you’ve already defined; automated annotations surface failure patterns in production that you didn’t know to write evals for. They are complementary.