This n8n workflow streamlines the process of managing new patient data in a healthcare CRM system. When a patient submits their information via a REST API (Webhook trigger), the workflow automatically processes, analyzes, and stores the data for easy retrieval and tracking. Key nodes include a Text Splitter that divides input into manageable chunks, embeddings generation using OpenAI, and vector storage via Weaviate to enable similarity searches. The workflow also includes a question-answering component with a language model (Anthropic) that interprets the data, updates a Google Sheet with the patient’s status, and sends error alerts via Slack in case of failures. This intelligent automation helps healthcare providers efficiently handle patient intake, improve data retrieval accuracy, and ensure prompt notifications.
Automated CRM Patient Intake and Data Processing Workflow
Node Count | 11 – 20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.embeddingsOpenAi, @n8n/n8n-nodes-langchain.lmChatAnthropic, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter, @n8n/n8n-nodes-langchain.toolVectorStore, @n8n/n8n-nodes-langchain.vectorStoreWeaviate, googleSheets, slack, stickyNote, webhook |
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