Important Note: This feature is available in Preview for select customers. During the Preview phase, AI Agent Evaluation is accessed inside the AI Agent Platform. At General Availability (GA), the experience will move to CXA Operations Center (formerly AI Trainer).
- Overview
- How it's Different
- How AI Agent Observability Helps
- Key Capabilities
- Impact
- Faster Troubleshooting
- Better Improvement Decisions
- Operational Transparency
- Important Information
Overview
AI Agent Observability gives administrators and supervisors end-to-end visibility into how AI Agents handle customer interactions. Through the new Session History view, teams can review past AI Agent conversations, validate behavior, audit performance, and make informed training decisions based on real interactions.
During the Preview phase, Session History is accessed inside the AI Agent Platform. At General Availability, the experience will move to the CXA Operations Center (formerly AI Trainer), providing a single, consistent place to observe and analyze AI Agent activity across channels.
How it's Different
Until now, teams have had limited visibility into what happened inside an AI Agent session. Reviewing outcomes often required piecing together information across multiple tools, making it difficult to understand why an interaction ended the way it did or how the AI Agent arrived at a given response.
This lack of transparency slowed down troubleshooting, made quality assurance harder, and limited the ability of trainers to continuously improve AI Agent performance.
How AI Agent Observability Helps
AI Agent Observability brings all relevant interaction data into a single, structured view. Admins and supervisors can quickly find the sessions that matter, drill into each conversation turn, and understand the AI Agent's reasoning step by step.
Whether the goal is to investigate a specific error, validate a recent configuration change, or identify training opportunities, Session History provides the context needed to act with confidence.
Key Capabilities
Session History
The Session History view lists recent AI Agent interactions with the key details needed to triage at a glance:
- Contact and Channel: The customer identifier and the channel used (Voice, Webchat, WhatsApp, Digital Connect, API, Autopilot, and more).
- Agent Orchestrator: The orchestrator that handled the interaction (e.g., Account management, Shipping information, FAQs).
- Date/Time & Duration: When the session occurred and how long it lasted.
- End of Automation: The outcome of the session (Completed, Escalated, Timeout, Error, Abandoned).
- Error count: a quick indicator of how many errors occurred during the session.
Click Details on any row to open the full session view, or use Export to download session data for offline analysis.
Advanced Filtering
To help navigate high interaction volumes, Session History includes a flexible filter panel. Users can narrow results by:
- When: Predefined ranges such as Last 20 days, or a custom date range.
- Channel: Voice, WhatsApp, Webchat, Digital Connect, and others.
- Agent Orchestrator: Filter by the specific orchestrator(s) that handled the interaction.
- End of Automation: Escalated, Completed, Timeout, Error, Abandoned.
- Interaction ID: Locate a specific session directly.
Filters can be combined, cleared individually, or reset all at once.
Session Details, Insights, and Errors
Opening a session reveals the full turn-by-turn conversation, along with contextual information such as Interaction ID and Session ID. Two dedicated views help focus the analysis:
- Insights: highlights key moments in the conversation, including the workflows used, inputs and outputs, and notable decisions made by the AI Agent.
- Errors: lists the errors and warnings that occurred during the session to support troubleshooting.
Per-turn latency metrics are also available, helping identify performance bottlenecks at the turn level.
Full Chain of Thought
For a deeper understanding of AI Agent behavior, the Thoughts panel exposes the full Chain of Thought behind each turn. This includes:
- The user message that started the turn.
- The sequence of agent decisions and transitions (e.g., Agent Retail Better Experience → Identify Customer Agent).
- Skill calls executed, with their inputs and outputs.
- Intermediate reasoning produced by the AI Agent.
- The final message returned to the customer.
This level of transparency helps teams confirm that the AI Agent is following expected logic, diagnose unexpected outcomes, and refine configurations with precision.
Impact
Faster Troubleshooting
Errors, latency, and full reasoning are available in one place, reducing the time needed to identify the root cause of an issue and apply a fix.
Better Improvement Decisions
By reviewing real AI Agent interactions end to end, admins and supervisors can identify patterns, validate behavior after configuration changes, and prioritize the improvements that will have the greatest impact.
Operational Transparency
Unified visibility across AI Agent sessions gives admins and supervisors a consistent, auditable view of automated interactions — within the AI Agent Platform during Preview, and in the CXA Operations Center at GA.
Important Information
- AI Agent Observability is available in Preview for select customers.
- During the Preview phase, Session History is accessed inside the AI Agent Platform.
- At General Availability, the experience will move to the CXA Operations Center (formerly AI Trainer).
- Following the Preview release, the remaining capabilities will be progressively rolled out to GA, such as Agentic Copilot Sessions.