AI Agent Analytics and Evaluation
An AI agent without metrics is a black box you pay for every month. Our agent analytics practice measures what each agent resolves, what each resolution costs, when it gets things wrong and how much it sells or saves, with automated evaluations that run before every change and dashboards leadership actually reads. It works for agents built by Possition or by any other vendor.
What this service covers
What we measure
- Containment rate and escalation rate, by intent.
- Accuracy and hallucinations: correct, sourced answers against an evaluation set.
- Cost per resolution: model, tokens, tool calls and infrastructure.
- p95 latency and uptime.
- Business impact: conversion, average order value, hours freed, CSAT.
- Drift: quality changes when data, models or user behavior change.
How we implement it
- Tracing for every conversation: input, retrieved context, tools used and answer.
- An evaluation set built from real conversations and edge cases, labeled with your team.
- Automated regression evals on every prompt, model or knowledge-base change.
- Statistical sampling for human review: just enough to keep a known margin of error.
- Operations and business dashboards, with alerts when a metric goes out of range.
Who it's for
Companies that already run agents in production —their own, Possition's or a platform's— and need to know whether they work, what they cost and where to improve them. Also teams about to launch an agent that want to set the quality bar before go-live.
What changes with agent analytics
| Criterion | No measurement | With agent analytics |
|---|---|---|
| What does resolving one inquiry cost? | You know the total invoice | Cost per resolution, by intent |
| When does it get things wrong? | When a customer complains | Continuous evaluation and alerts |
| Switching models or prompts | Tested in production | Automated regression before release |
| Business impact | Anecdotes | Measured conversion, hours and CSAT |
Implementation process
- 1
Diagnostic
We analyze your process and tell you what to automate, how, and what return to expect.
- 2
Implementation
We build the solution connected to your systems, with working deliveries and real tests.
- 3
Operation and improvement
We leave it running, train your team, and measure results.
The full detail, with deliverables per stage, is in how we work.
Frequently asked questions
Does it work with agents Possition didn't build?
Yes. We instrument the existing agent or read its logs, build the evaluation set and the dashboards, without replacing the platform.
What is an evaluation set?
A set of real questions and edge cases with their expected answers, validated by your team. Every version of the agent is scored against it before it reaches customers.
How soon do we get the first metrics?
With log access, operations and cost metrics are live in one to two weeks; the full evaluation set takes three to four.
Running an agent in production without knowing what each answer costs?
Tell us which agent you use and we'll put together the measurement plan.