AI Agent Observability

Your AI agents are live. Who's checking what they say?

Most contact centres can tell you their bot's containment rate. Almost none can tell you whether the answers were right, where it failed, or what to fix. evaluagent evaluates every conversation your AI agents have, against your standard, compared to your best human agents. So you can prove the AI is working, not just promise it.

Observability

See what your AI agents are actually saying.

Every CSAT dip, every spike in handovers, every angry customer typically starts somewhere upstream. evaluagent helps you trace it back to the bot conversation that caused it, surfacing friction points, root causes and escalation triggers that you missed, so you can improve it for next time.

INDEPENDENT BY DESIGN

Don't solely rely on your bot vendor's metrics.

evaluagent sits above the agent layer, not inside it. Whether the bot was built by Cognigy, Sierra, Decagon or your own team, we hold every conversation to the same standard, scored by the same engine that runs your human QA programme to provide you with an independent view of Quality across every interaction - Human or AI.

A second opinion on every conversation

Your bot reports it resolved the contact. evaluagent tells you whether the customer actually got what they came for, and met your own definitions of good.

One standard across every vendor

Most contact centres now run more than one bot, and they're moving. Cross-vendor reporting grades Cognigy, Sierra, Decagon and your humans against the same definition of quality, so you stop comparing apples to whatever the next vendor calls "Resolved".

Your data, your benchmarks, your call

Conversations, scores and trend reporting sit in evaluagent, not in the bot platform. When you switch vendor, the historical quality record comes with you, and the evidence for regulators stays yours.

Conversation-Level Intelligence

Know which intents your bots handle well, and which ones cost you customers.

evaluagent analyses every conversation against xNPS, xRepeats, xVulnerability and even custom topics, grouped together to provide you with intent-level performance. See which intents resolve cleanly, which generate frustration, and which leave your human agents picking up an unrecoverable handover.

From containment metrics to actual quality — in weeks, not quarters.

Bring a week of your bot's conversations. We'll show you what's working, what's hallucinating, and where the silent failures are.

HALLUCINATION & RISK DETECTION

Catch fabrications and off-policy responses before they become fires

evaluagent flags hallucinated content, off-policy advice and compliance breaches before they reach a regulator's desk, with knowledge base integration that grades every response against your source of truth so you can stop risks in their tracks.

CONTINUOUS IMPROVEMENT

See what's working, what needs attention, and where your AI agents can go next.

evaluagent shows you which intents your bots are handling well, which ones need a prompt tweak or a content update, and which intents the bot is ready to take on next. The reporting suite makes the wins visible and the gaps actionable. Alerts surface the things that can't wait. And when you're ready to expand bot coverage to the next intent, the next channel or the next workflow, you've got the evidence base to do it with confidence.

Questions QA leaders ask before they buy

Common questions from QA leaders, ops managers, and contact centre directors evaluating evaluagent.

Why does AI agent quality need its own governance layer?
AI agents are non-deterministic. They make different decisions in similar conversations, they invent answers when their training thins out, and they change behaviour every time the vendor ships a model update. The governance question is no longer “did the agent follow the process,” it’s “is the system producing acceptable outcomes today, and can you prove it.” That is a different discipline, and it needs a platform built for it.

Why now? Couldn't this wait until our AI deployment is more mature?
62% of enterprises deploying AI agents have no assurance framework in place. 1 in 4 brands expect service quality to dip as AI deployment accelerates. The pattern across every CX leader we speak to is the same. Bots shipped faster than the governance around them, and the gap is now visible to the board, the regulator or the customer. The cost of catching that gap after a regulatory finding is an order of magnitude higher than catching it now.

Why can't I just trust my bot vendor's own metrics?
You can trust them for the question they answer, which is “did the bot contain the conversation.” But we would always recommend getting a second opinion for matters that relate to the more subjective measures; like empathy, process adherence or resolution. By doing so, you can answer the question most boards are actually asking, which is “did the bot deliver a quality outcome for the customer.”

We believe that a regulator, a chief risk officer or a CFO underwriting AI spend needs an independent evidence base, and evaluagent is built to be exactly that.

Every conversation you don't evaluate is a risk you can't see.

evaluagent evaluates every conversation your AI agents have, against your standard of a great customer experience, and compares their performance to your best human agents. One independent platform. One quality picture across humans and bots. So you can ship AI confidently, and collect the receipts to prove it's working.