Frequently asked questions
AI agent monitoring, recovery, and improvement
Practical answers for operations teams responsible for production voice agents, support agents, and other customer-facing AI systems.
What is AI agent monitoring?
AI agent monitoring is the process of identifying where a production agent gets stuck, misunderstands a customer, fails to complete a task, misses a handoff, or produces an outcome that does not match the state of the business system.
How is FieldSignal different from call analytics or LLM observability?
Call analytics and observability tools usually show transcripts, latency, tool calls, and technical errors. FieldSignal is designed for operations teams that also need to know whether the customer request was completed, whether follow-up is required, and what should happen after a failure is found.
Which AI agents can FieldSignal monitor?
FieldSignal is starting with customer-facing voice and conversational agents. The operating model also applies to other agents that accept work, call tools, update business systems, and sometimes require human intervention.
What happens when an agent interaction needs attention?
FieldSignal can surface the case for review and trigger a predefined recovery path, such as assigning an operator, creating a ticket, scheduling a callback, retrying a workflow, or notifying the relevant team.
How do operator corrections improve the agent?
An operator explains what should have happened in ordinary language. FieldSignal can turn that correction into a proposed regression test, prompt change, tool guardrail, or operating policy for review and validation.
Does FieldSignal update production agents automatically?
Changes can follow review, approval, validation, and staged deployment. The goal is not uncontrolled self-modification. The goal is to help teams move from a real production failure to a tested and traceable improvement.
What is included in an Operator Review?
The Operator Review is a 30-minute working session covering how your team currently discovers agent issues, handles unresolved customer work, escalates cases, captures operator corrections, and feeds those corrections back into agent improvement.