How Included Health Built Federated Agents for Healthcare Navigation with Deep Agents and LangGraph

Included Health uses Dot, an AI-powered healthcare guide built with LangGraph and Deep Agents, to help employer and health-plan members navigate medical, financial, and administrative needs across services such as virtual care, behavioral health, specialty care, and scheduling. The platform replaces rigid decision-tree approaches with conversational agents that can interpret individual context, identify emergencies early, ask relevant follow-up questions, and recommend appropriate care while maintaining personalization at scale. Its federated “supergraph” architecture allows separate product teams to own specialized workflows while shared prompts, skills, context management, and a virtual filesystem preserve consistent tone and prevent members from repeating information when moving between services. Skills act as a registry of care capabilities, eligibility rules, and edge cases, while clinical reviewers continuously assess routing recommendations and refine the system. Human advocates can take over uncertain conversations through durable execution, after which the agent resumes with the full interaction history, and the company is exploring parallel agent support for advocates. LangSmith supports clinical review, operational metrics, and simulations used to validate system changes; following its August launch, Dot reportedly produced a 75% increase in chat engagement, clinical recommendation agreement above its 95% target, and detection of more than 99% of high-risk situations.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.