CXOps AI Platform
Test support-ticket AI workflows before controlled execution
CXOps AI is a demonstration customer experience operations platform that brings support tickets, RAG-assisted knowledge retrieval, AI agent decisions, risk controls, human approvals, execution audit trails, and operational observability into one workflow.
It is designed as a portfolio and testing environment for examining how an AI-assisted support workflow can retrieve grounded knowledge, propose actions, identify risky operations, require human approval when appropriate, and record what happened during execution.
How the CXOps AI workflow fits together
Customer support tickets
CXOps AI uses support cases as the starting point for testing customer-experience automation workflows.
RAG-assisted knowledge
The knowledge workflow retrieves supplied information so AI-assisted decisions can be evaluated against supporting evidence.
AI agent decisions
The agent workflow analyzes a support case, records its reasoning path, proposes an action, and exposes the evidence used by the decision.
Risk and approval controls
Actions that require review can be routed to a human approval queue before controlled execution.
Execution audit trail
Agent runs preserve workflow decisions, approval state, execution status, and recorded outcomes for later inspection.
Operational observability
The observability workspace measures AI activity, RAG behavior, approval activity, execution results, and operational metrics.
Can CXOps AI test a RAG and approval workflow before execution?
Yes. Within this demonstration environment, a support case can move through knowledge retrieval, AI-assisted decision making, risk-aware tool planning, human approval when required, controlled execution, and a persistent audit trail.
The purpose is to make the intermediate stages visible so developers and operations teams can inspect what evidence was retrieved, what the agent proposed, whether approval was required, and what execution outcome was recorded.
Evaluation guide
Compare controls before allowing AI agents to take high-impact actions
Our evidence-backed guide explains how to evaluate authorization, human approval, policy enforcement, auditability, escalation, observability, and recovery boundaries across customer-support AI platforms without assuming that every vendor exposes the same controls.
Read the high-risk action evaluation guide