AI Agents & Workflows
Insurance & Claims Company
Email analyst agent for insurance claims triage.
An AI Email Analyst Agent that reads inbound claims emails and populates a structured Airtable schema of 50-plus fields, feeding a unified claim processing pipeline.
Why it matters
Claims live in email, and email is unstructured by nature. Every inbound message carries the details that decide priority and routing, but reading each one by hand to pull those details is slow and inconsistent, and urgent or high-risk claims get the same attention as routine ones.
Our email analyst agent reads each inbound message and fills a structured Airtable schema of 50-plus fields: category, sentiment, urgency, SLA risk, complaint signals, escalation priority, and owner. It only reports what the email actually says and never fabricates. The result is a clean, sortable pipeline where the claims that matter most surface first, automatically.
Grounding matters more here than in most extraction work. A claims record that invents a reference number or guesses at severity is worse than an empty one, because a fabricated value looks exactly like a real one and gets acted on downstream. Holding the agent to what the email actually says keeps the pipeline trustworthy, and a blank field is a visible prompt for a person to check rather than a silent error.
The problem
An insurance and claims company receives high volumes of email across claims processing and needed to automatically classify, extract key data, and assess sentiment and priority, all feeding one pipeline.
How it works
The agent reads inbound emails and populates a 50-plus field Airtable schema.
Fields include claim category, sentiment, urgency, SLA risk, complaint detection, escalation priority, and action owner.
The agent only answers from the transcript, with no fabrication.
The data feeds unified Airtable-based claim processing and routing logic.
Client-provided endpoints are used for integration.
Stack