QyrosCloud built a conversational agentic AI system for InformINS that modernizes FNOL intake using Amazon Bedrock and LangChain agents. The platform enables policyholders to report claims through natural conversation, with AI agents automatically extracting structured data, validating policy details, and submitting claims — replacing manual form-based intake with an intelligent, guided experience.
What was at stake.
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.
“InformINS partnered with QyrosCloud to replace its rigid, form-based FNOL process with an AI-driven conversational chatbot on AWS. Powered by Amazon Bedrock and LangChain, the solution dynamically adapts questions, submits claims via API, and enables seamless human escalation—demonstrating a faster, more scalable approach to FNOL intake.”
How we solved it.
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.
- 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.
- 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.
- 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.
- 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.
- 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.
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
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
“This engagement required us to balance speed with compliance rigor. We deployed infrastructure-as-code from day one, automated evidence collection across the environment, and delivered a production-ready architecture that passed security review on the first attempt.”
The results speak for themselves.
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.
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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