You review a sample of calls, but the important cases may be elsewhere.
Sampling is useful, but it does not reliably surface every conversation that needs follow-up.
AI agent monitoring and operations
See which customer conversations need attention.
Teams running AI agents often rely on call sampling, support tickets, and customer feedback to understand what went wrong. FieldSignal helps you find unresolved interactions, recover unfinished work, and improve how the agent handles similar cases next time.
FieldSignal is an AI agent monitoring and operations platform in private beta for teams already running customer-facing voice and conversational agents.
FieldSignal Operations
Operations queue
Customer interactions requiring attention
Unresolved18+4 today
Recovered67
Awaiting review9
Cases needing action
Customer repeated the case number three timesCustomer Intake Agent · 3 min ago
FrustratedOpen caseService address could not be verifiedAddress Verification Agent · 11 min ago
Needs reviewReviewTicketing tool failed after customer confirmationCase Routing Agent · 18 min ago
Follow-upEscalateTicket generation correction ready for validationTicket Creation Agent · 17 similar cases
ReviewView changeCommon patterns we hear from operations teams
Manual call reviewSampling conversations to understand where customers struggle
Late discoveryLearning about issues through follow-up contacts or support tickets
Recurring issuesCorrecting the same type of problem more than once
What operators still need to know
A completed call does not always mean the customer's request was completed.
Some issues only become visible after the customer contacts you again.
The first clear signal may be a repeated call, a missed appointment, a support ticket, or a request for human help.
The conversation may sound resolved even when the next step is missing.
The customer heard that a ticket was created or a callback was arranged, but the expected record never appeared.
Your team resolves the case, but the correction is difficult to reuse.
The useful context often remains in a ticket, Slack thread, or an operator's notes instead of becoming a repeatable improvement.
From issue to improvement
Find the interaction, resolve the case, and carry the learning forward.
FieldSignal connects the immediate operational response with the longer-term work of improving how the agent behaves in similar situations.
Resolve the case. Improve the agent.Customer recovery and agent improvement stay connected.
Monitor
Find unfinished work, missing data, failed handoffs, and broken tool calls.
Rectify
Recover the customer, retry the workflow, or route the case to the right operator.
Learn
Capture what the operator did differently and what should happen next time.
Generate
Create the regression test, prompt change, tool guardrail, or policy.
Validate
Test the change against the original failure, similar cases, and existing tests.
Update production
Deploy the approved improvement and confirm the failure rate actually drops.
FieldSignal keeps the operational response and the improvement process connected, so useful corrections are easier to reuse.
Operator knowledge matters
Your operators often know the right next step.
They are already identifying when a case should go to a human, when information is still missing, and when a customer needs a callback. FieldSignal helps turn those observations into reusable improvements.
Operator correction
“Never confirm the case until the ticketing system returns a case ID. If the tool times out, explain that the case is not yet created and arrange follow-up.”
Regression testTicket creation timeout scenario
Prompt changeRequire confirmed case ID
Tool guardrailUnknown status cannot confirm
Recovery policyCreate follow-up task
Field notes
Practical lessons from operating production agents.
The FieldSignal blog will cover agent monitoring, unresolved customer work, operational playbooks, human correction, evaluation, and safe production improvement.
Visit the blogFrequently 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.
Early beta
Review how your team currently operates production agents.
The Operator Review is a 30-minute working session for teams already running customer-facing agents and looking for a clearer view of unresolved work and recurring issues.
- Understand how issues are currently discovered
- Identify which conversations still depend on manual review
- Review what happens when a customer needs follow-up
- See how operator corrections become lasting improvements
Book an Operator Review
No sales deck. No commitment. Just an honest conversation about how you are running agents today.
30 minutesFocused on your current production setup
Practical reviewMonitoring, recovery, and recurring failure patterns