AI Agent Conversation & Performance Diagnostics
See exactly where your agents fail, loop, or lose the user.
Companies deploying AI agents increasingly have thousands or millions of interactions but limited visibility into what actually makes agents succeed or fail. Teams running autonomous agents for customer support, sales qualification, or internal workflows struggle to evaluate whether agents are resolving user queries or asserting incorrect advice. Product teams can upload raw multi-turn conversation logs, latency metrics, satisfaction scores, and escalation events, then map nuanced behavior concepts across free-text sessions with a consistency manual review at scale can never achieve.
That includes hallucination precursor language, tool misuse patterns, prompt injection attempts, refusal edge cases, frustration escalation signals, and task abandonment themes. The platform maps the conversational journey, evaluating the exact topic branches where agents fail or loop endlessly. By exploring predictive power scores and ranked findings, developers can pinpoint prompt failures, optimize tool routing, and hand leadership an agent quality report they can act on before the next model release.
AI Topic Mapping
Use Steeped AI's AI topic mapping to categorize user intent and agent response themes across unstructured chat transcripts, isolating recurring failure points. Concepts like hallucination precursor language and refusal edge cases become countable columns instead of anecdotes from a spot check.
Customer Journey Mapping
Use Steeped AI's journey mapping to turn multi-turn agent conversations into structured, measurable journey stages, identifying exactly where users abandon chats. The turn that breaks the session stops being a guess and becomes a coordinate on the map.
Long Text or ID Examples
Trace any agent failure metric down to the raw sessions behind it with long text or ID examples, with the exact turns that triggered the finding highlighted. An engineer reads the conversation that broke, not a percentage describing it.
Predictive Power Score
Steeped AI's regression predictive power identifies which agent behaviors, such as latency over three seconds or repeated clarification prompts, most strongly predict escalation to a human. Prompt and routing fixes then target the behavior that actually costs you the resolution.
The insights are already in your data.
Ask your data anything. Get real findings ranked by impact, with AI reports your team can present and share on the spot.