First Notice of Loss Voice AI (FNOL)

FNOL intake is constrained by call center capacity and inconsistent questioning. Manual note-taking creates incomplete records, rework, and slower claim triage and handoffs.

FNOL and triage are often slowed by limited availability, long wait times, and inconsistent information capture across agents and channels. Customers may provide details in unstructured ways, leading to missing critical fields, unclear timelines, and repeated follow-ups. Manual note-taking and transcription introduce errors and increase operational effort, while variability in questioning affects data completeness and downstream processing. In peak events, intake backlogs delay claim initiation and triage decisions. Finally, teams need a controlled way to capture, store, and share FNOL records with full traceability and smooth escalation to human adjusters when required.

Use an intelligent voice assistant to guide FNOL conversations and capture structured incident data in real time. Automate triage-ready FNOL records and seamlessly hand off to claims teams when human intervention is needed.

The solution provides an always-on voice FNOL experience that guides customers through a consistent intake flow, captures incident details, and converts responses into a structured FNOL record. Voice interactions are orchestrated through a controlled workflow that performs real-time transcription, extracts key entities, validates completeness, and generates a triage-ready case packet. High-confidence submissions can be routed directly into claims intake, while flagged or complex scenarios are escalated to human adjusters with full context. All artifacts—audio, transcripts, and structured records—are stored securely with traceability for compliance and audit needs.

Improves FNOL speed and quality by capturing complete incident details via voice, generating structured records, and enabling seamless triage handoffs.

Reduces wait times and accelerates FNOL intake through always-on voice automation and straight-through case creation.

Standardizes questioning and produces structured FNOL records, reducing missing fields, rework, and downstream clarification cycles.

Escalates complex or low-confidence cases to adjusters with full transcript context and validation results for faster resolution.

Delivers consistent FNOL questioning through an intelligent voice interface, ensuring critical fields are captured (who/what/when/where) without relying on agent variability. Built on AWS services for scalability, it reduces wait times and supports peak-event intake while maintaining a controlled, repeatable customer experience.

Converts voice responses into a structured FNOL record with entity extraction, completeness checks, and confidence indicators. Produces a triage-ready packet that can be routed directly into claims intake or escalated to human adjusters with full context (audio, transcript, validation results), improving resolution speed and accuracy.

Brillio reinvents FNOL and triage on AWS with an always-on voice experience that guides customers through consistent incident questioning and generates a structured FNOL record in real time. The solution leverages AWS voice and AI services to transcribe responses, extract key details, validate completeness, and package a triage-ready case for claims intake. High-confidence submissions can flow straight-through to downstream systems, while complex or low-confidence cases are escalated to human adjusters with full context. Secure storage of audio, transcripts, and records supports traceability, compliance, and operational resilience during peak-volume events.

AWS Native Services Utilized: AWS Lambda AI, Amazon Bedrock, AWS Amplify, Aamzon API Gateway

A large national insurer faced FNOL backlogs during peak periods, long hold times, and inconsistent data capture across agents. Manual note-taking led to missing fields and repeated follow-ups, delaying claim creation and triage while increasing customer frustration.

Brillio implemented an AWS-based voice FNOL workflow to guide questioning, transcribe calls in real time, extract and structure incident details, and generate triage-ready FNOL packets. Exceptions were routed to adjusters with full transcripts and validation signals.

The insurer improved FNOL speed and completeness, reduced rework caused by missing or inconsistent information, and enabled smoother handoffs to claims teams. Intake reliability improved during volume surges, with better traceability and governance of customer interactions.