Your AI made a thousand decisions today. See every one.

Your AI is handling more customer conversations than ever. But basic success metrics like resolution rates, CSAT scores, and handle times only offer a macro view of AI performance.

Here's what they don't tell you:

• What AI actually did in a specific conversation

• What instructions it followed

• What knowledge it pulled from

• Why it decided to hand off instead of respond

You create blind spots when you see outcomes without the decisions that got you there. When something goes wrong, you're left guessing.

As AI takes on more complex, higher-stakes conversations, those blind spots get expensive. That's why modern CX teams need more than aggregate metrics. They need to trace what happened in a specific conversation, understand why, and fix it right away.

What Gladly's Conversation Review Panel does

Gladly's Conversation Review Panel shows you exactly what AI did in any conversation and why. Open any conversation, click an AI response, and see the step-by-step decisions: which instructions it followed, what knowledge it gathered, what rules fired, and whether it responded or handed off.

You only see what you can change. The panel doesn't show internal AI system prompts or model settings you can't touch. It only shows the things you control — like Guide instructions, knowledge sources, and quality checks — all with direct links to edit them.

See exactly what AI did and why

The Conversation Review Panel gives you three ways to investigate AI performance, from high-level assessment to deep technical debugging.

Review conversations and spot patterns

Every AI-handled conversation is available for review. Rate it with a thumbs up or thumbs down, then add comments on what worked or didn't.

All submitted reviews feed into a centralized log, giving your team a single place to spot patterns over time — recurring issues with a specific topic, common handoff triggers, or quality trends across conversations.

Example: You're doing a weekly QA pass. You review 20 conversations and leave ratings and notes. Over a few weeks, the log reveals that one topic area consistently gets flagged. That's a signal. Now you know exactly where to focus.

Trace AI's decision path

Click on any AI response and see the decisions AI made, in plain language. The Summary view shows you the instructions the AI followed and the path it navigated — displayed as a visual breadcrumb.

For each step, you'll see:

• The action that ran

• The specific sources retrieved

• The rules evaluated and which ones fired

• The guidance AI followed

• What happened next

Every element within your control includes a direct link to edit it.

Example: Your AI gave a customer an incorrect answer. You click the response, and the decision path shows the AI following the right instructions and the right path — but it retrieved an outdated knowledge source. You click the link to the source and update it on the spot. You've just identified and solved the issue in minutes instead of hours or days.

Investigate with the full technical trace

For deeper investigation, the Debug view shows every algorithm component that fired, in execution order. You see each component as a card with collapsible sections where you can clearly see what went in and what came out.

You can jump directly to any component from clickable badges in a trace summary. Color-coded labels mark transitions: when a new customer message triggers a processing run, when AI navigates between paths, or when a handoff occurs. When something is configurable, direct edit links take you straight to the relevant setting.

Example: Your AI handed off a conversation it should have resolved. The trace shows that a quality check failed on the generated response — specifically, it flagged an "implied mutation" where AI appeared to promise something it shouldn't have. You click through to the quality check configuration, adjust the threshold, and the next set of conversations parses correctly.

How this fits the AI improvement lifecycle

The Conversation Review Panel is part of the observing layer in how CX teams continuously manage their AI. This cycle is how CX teams manage and iterate on their AI — with transparency into every decision, and control that builds trust in it over time.

• Configure: Define how your AI should behave in plain language — what it should say, how it should respond, and what rules it should follow.

• Test: Validate AI behavior at scale before it reaches real customers.

• Deploy: Deploy with control. Version your AI, test variations, and roll back instantly if something isn't working.

• Observe: Review AI decisions in production — what it did, why it did it, and where it fell short.

• Improve: Close the loop. AI surfaces suggested changes so you can continuously improve performance.

The Conversation Review Panel connects monitoring directly to improvement. You review conversations and spot where things broke — or where there's room to improve. You click through to the instructions, the knowledge configuration, or the quality check settings and make the change. Then you review the next set of conversations to see whether it worked.

This is how AI gets smarter — not through one big training push, but through a continuous cycle of monitoring, learning, and adjusting.

Why CX teams need this now

Full visibility into AI decisions changes how CX teams operate.

CX teams own their AI

The Conversation Review Panel gives CX teams unprecedented control. CX leaders and AI ops managers can trace what happened in any conversation, understand why, and make changes — without filing a ticket or waiting for support.

AI is no longer a black box

Every AI decision now has a traceable path. When leadership asks "what is our AI doing?" or "why did that happen?", your team has a clear answer.

Improvement becomes targeted

When you can see exactly where AI went wrong, you know exactly what needs to change. Improvement becomes targeted and efficient — no more trial and error.

Expand AI's role with confidence

The more visibility you have into how AI handles conversations, the more confidently you can give it more to do. The Conversation Review Panel builds the trust that lets teams move faster.

Transparency is how AI earns the right to scale

AI without transparency is AI without control. And AI without control is AI you can't scale.

The Conversation Review Panel changes that. Every decision becomes traceable and every issue becomes fixable. Every conversation is an opportunity to make your AI better.

Your AI made a thousand decisions today. Now you can see every one — and know exactly what to do about it.