InformINS Modernizes FNOL Intake with Conversational Agentic AI with Bedrock
Customer Challenge
FNOL (First Notice of Loss) is a critical entry point in the insurance claims lifecycle. The speed and accuracy of FNOL intake directly impact:
- customer satisfaction
- claim processing timelines
- operational efficiency
- data quality for downstream workflows
Informins sought to modernize this process by introducing AI-driven automation while ensuring the platform could operate reliably at scale. However, its existing FNOL workflow relied on traditional, form-based data entry.
InformINS needed to validate whether AI-driven conversational intake could replace forms while preserving accuracy, compliance, and operational control.
Key Challenges
- Rigid FNOL Experience
- Static forms could not adapt dynamically to claimant responses.
- Inefficient Data Collection
- Users were forced through fixed question paths regardless of relevance.
- Limited Customer Experience
- The process lacked conversational guidance and real-time clarification.
- No AI Foundation for Future Channels
- The legacy approach was not extensible to voice or intelligent automation.
- Limited Scalability
- The system struggled to handle spikes in claim volume, concurrent user interactions and real-time processing requirements
- Lack of Operational Visibility
- The platform lacked centralized monitoring for conversation success rates, system latency and failure or fallback scenarios
QyrosCloud Solution
QyrosCloud designed and implemented a containerized, AI-powered FNOL chatbot on AWS, focused on conversational accuracy, flexibility, and future extensibility.
The solution leveraged Amazon Bedrock, LangChain agents, and a web-based chat interface, while maintaining tight control over prompts, escalation logic, and data submission.
1Conversational FNOL Intake with Generative AI
- Implemented a text-based AI chatbot that guides users through FNOL intake.
- Dynamically adjusted questions based on prior responses.
- Followed InformINS’ existing FNOL question flow for accuracy and compliance.
2Agentic Orchestration with LangChain
- Used LangChain Agents with Tools to manage conversation flow and decision logic.
- Determined when sufficient FNOL data had been collected.
- Controlled escalation paths when human assistance was required.
3Amazon Bedrock–Powered Intelligence
- Leveraged Claude 3 Sonnet via Amazon Bedrock for conversational reasoning.
- Centralized system prompts stored securely in AWS Systems Manager Parameter Store, enabling prompt updates without code changes.
4API Submission & Escalation Handling
- Submitted completed FNOL data to a backend Mock API (AWS Lambda) for validation.
- Confirmed successful transmission of FNOL details to downstream systems.
- Provided predefined escalation messaging and call-center handoff when needed.
5Secure, Containerized AWS Deployment
- Deployed the solution as a Dockerized application on Amazon EC2.
- Delivered a web-based chat interface using Chainlit.
- Ensured consistent deployment and simplified environment management.
6Proactive Application Monitoring
A centralized observability layer was implemented using Amazon CloudWatch.
Monitored KPIs
- FNOL submission latency
- AI response time
- conversation completion rate
- fallback/error rate
- system throughput
7Governance and Compliance Controls
QyrosCloud implemented governance mechanisms using Bedrock and AWS-native services.
Controls
- structured prompt templates
- guardrails for safe and compliant responses
- audit logging of interactions
- controlled data capture flows
Results & Business Impact
Partnering with QyrosCloud enabled InformINS to validate conversational AI as a viable By replacing static FNOL forms with an AI-driven conversational intake system, InformINS significantly improved intake efficiency, scalability, and operational visibility while maintaining structured data integrity.
⏱ 60–75% reduction in FNOL completion time
Dynamic questioning eliminated irrelevant form fields and reduced claimant friction.
📉 40–55% reduction in manual intake review effort
Structured AI extraction reduced downstream correction and clarification cycles.
💬 100% dynamic question routing
The conversational engine adapts in real time based on user responses, eliminating fixed-path logic constraints.
📈 Improved data completeness and consistency
LLM-guided extraction ensured required fields were collected before submission, reducing incomplete FNOL submissions.
🔄 Instant API submission and validation
Completed FNOL reports are transmitted in near real-time, accelerating claims initiation.
⚡ Scalable intake without infrastructure overhead
Containerized deployment on AWS enables horizontal scaling as FNOL volume increases.
🔐 Centralized prompt control and governance
Secure prompt management through AWS Systems Manager allows iterative improvements without code redeployment.
Technology Stack
AWS Services
AI & Orchestration:
Frontend & Runtime
Integration
About InformINS
InformINS provides advanced, scalable software and analytics solutions for the property & casualty insurance industry. By adopting AI-driven FNOL workflows, InformINS is improving customer experience while laying the groundwork for intelligent, automated claims processing.
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