customer_support · healthcare · workflow
OpenRecovery builds a multi-agent AI recovery assistant with LangGraph and LangSmith
Addiction recovery support faces a gap between costly inpatient care and generic self-help programs, leaving those struggling with addiction without accessible, expert-level, personalized guidance.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · User sends text or voice message
The AI assistant provides personalized, 24/7 support via text and voice.
Tools used
LangGraphLangSmithLangGraph PlatformLangGraph Studio
Outcome
OpenRecovery built a sophisticated, scalable multi-agent mobile application that adapts to individual users' recovery journeys, with human-in-the-loop features for trust and LangSmith-accelerated development.
Grounding & classification
Source type: technical build writeup
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agentic workflowconversational aimulti agent workflowchat transcripthuman review describednamed customerproduction runtime claimedtools describedworkflow describedhealthcaretechnical build writeupcustomer supportagentic task executionai draft human approvalhuman review queue