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Linked challenge: Orchestrate Insurance Policy Automation

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Linked challenge

Orchestrate Insurance Policy Automation

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Develop at least two Semantic Kernel native functions that simulate interactions with an enterprise CRM (e.g., retrieve client history, update policy status). Implement the 'Policy Customizer' agent to use these tools via the Semantic Kernel planner to generate a policy and update the client record.

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This prompt is mostly narrative and instruction-driven, so adapt examples and output constraints before you rewrite the structure.

Linked challenge

Orchestrate Insurance Policy Automation

There is potential for generative AI to revolutionize complex enterprise workflows. This challenge focuses on building a sophisticated multi-agent system to automate aspects of the insurance policy lifecycle, specifically dynamic risk assessment and personalized policy generation. Your system will use Claude Sonnet 4 for efficient reasoning over vast policy documents and external data. It will leverage Haystack for advanced Retrieval-Augmented Generation (RAG) to ensure accuracy and compliance, and Semantic Kernel for robust tool integration with legacy enterprise systems and structured databases. The goal is to create a hybrid reasoning system that combines the flexibility of LLMs with structured rules and real-time external data, adapting to evolving risk profiles and regulatory changes.

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