How JD Insurance Uses AI Agents to Automate the Entire Insurance Supply Chain

This article explains JD Insurance's end‑to‑end AI agent methodology, from scenario selection and goal definition through economic benefit formulas, domain‑specific large‑model fine‑tuning, knowledge‑base integration, multi‑agent planning strategies, reinforcement‑learning driven evolution, and concrete implementations for pricing, fulfillment, and risk control across the insurance value chain.

AI Agentsinsurance automationlarge language models

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How JD Insurance Uses AI Agents to Automate the Entire Insurance Supply Chain

DataFunTalk

Oct 29, 2025 · Artificial Intelligence

Voice Agents Transform Gaming & Insurance: Real‑World Lessons from Silicon Valley

In a Silicon Valley tech conference, Mu Shen shared how voice agents—real‑time, task‑oriented AI—were applied to an open‑world game as an AI NPC and to a Fortune‑500 insurer as an AI tele‑salesperson, revealing technical challenges, model architectures, training strategies, evaluation methods, and key lessons for future deployments.

Model architecturegame AIinsurance automation

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Voice Agents Transform Gaming & Insurance: Real‑World Lessons from Silicon Valley

AntTech

Mar 18, 2025 · Artificial Intelligence

MoLE: Decoding by Mixture of Layer Experts Alleviates Hallucination in Large Vision-Language Models

Researchers from Ant Insurance and Zhejiang University propose MoLE, a Mixture of Layer Experts decoding method that reduces hallucinations in large vision‑language models, demonstrating state‑of‑the‑art performance on LVLM benchmarks and enabling reliable end‑to‑end medical‑record‑to‑claim automation.

AIMixture of ExpertsVision-Language Models

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MoLE: Decoding by Mixture of Layer Experts Alleviates Hallucination in Large Vision-Language Models