Kustomer, a customer experience platform provider, has introduced the Kustomer AI automation assistant and the Kustomer AI observability assistant to help customer experience teams gain immediate clarity into what is powering their customer experience, from workflows, rules, and routing logic to the behavior of AI agents in live interactions.
"As automation strategies mature and AI adoption accelerates, teams need intelligent tooling to manage increasing complexity," said Jeremy Suriel, chief technology officer of Kustomer, in a statement. "This assistant analyzes your entire automation setup in seconds, detecting conflicts, surfacing optimization opportunities, and helping maintain best practices. It's the kind of AI capability that becomes more valuable as you scale."
The Kustomer AI automation assistant reviews all deterministic logic, including workflows, rules, and routing paths, and flags redundancies, contradictions, and unreachable logic. The Kustomer AI observability assistant focuses on non-deterministic behavior, analyzing AI agent execution traces and providing plain language explanations of what happened, why it happened, and how to improve performance. Because these AI Assistants are built directly into Kustomer's unified data model and orchestration engine, they can provide real-time insights across the entire customer experience, from workflows and automations to agent behavior and customer interactions. This embedded architecture gives CX leaders a connected view of their operations paired with clear, actionable guidance.
Key capabilities of the AI automation assistant include the following:
- Cross-product automation analysis to map the workflows, business rules, routing paths, and queue logic.
- Conflict and redundancy detection to surface contradictions, unreachable paths, dead ends, drift, and logic that will never run.
- Unified, AI-native foundation that operates on Kustomer's unified data model and orchestration engine for a holistic view across products and teams.
Key capabilities of the AI observability assistant include the following:
- Agent trace analysis to summarize what an AI agent did (reasoning, decisions, tool calls, knowledge sources) in everyday language.
- Root-cause identification to pinpoint issues like bad tool calls, ambiguous instructions, missing context, or incorrect knowledge selection.
- Recommended next steps to improve accuracy and consistency.
- Admins-only visibility spanning AI for Reps and AI Agents for Customers to strengthen governance.
With these launches, Kustomer now offers the following six AI Assistants, all built natively into the platform:
- AI automation assistant, to analyze and optimize every workflow, rule, queue, and route flow.
- AI observability assistant to review post-deployment execution traces and identify error root causes for AI debugging.
- AI knowledge base assistant to transform old knowledge bases into living, self-improving knowledge layer giving context to customers and agents (AI and human).
- AI Agent team assistant for managing one intelligent AI org chart.
- AI workflow assistant powered by AI.
- AI search assistant powered by conversational AI.