Answer patient enquiries for a clinic by chat
An n8n and Gemini agent receives patient chat messages, keeps context, uses clinic info from Google Sheets and responds to enquiries.
Built agents for a wholesale food distributor that ran on Excel, calls and email, including inventory tracking and a copywriter agent for outreach emails.
Built agents for a wholesale food distributor that ran on Excel, calls and email, including inventory tracking and a copywriter agent for outreach emails.
They started with a wholesaler that ran on Excel, phone calls, texts, emails, and manual follow-ups. The setup chained simple agents: scrape local businesses from Google Maps by ZIP code, generate segmented cold-email copy from scraped YouTube transcript examples, find and verify emails with Apollo, Apify, and Million Verifier, send campaigns through warmed inboxes in Aerosend and Smartlead, and flag inventory reorders from rules and sales history; a human still approved purchases.
In 4 months, monthly revenue rose from about $22K to $45K, leads contacted from about 120 to 1,500+, verified local leads to around 900 a month, and new customers from 3–4 to 12–15 monthly. The inventory piece was intentionally basic, using rules plus historical sales velocity rather than advanced optimization.
They say the automation worked best because the tools had solid APIs, and the reorder system’s first version was simple rules with human approval, not a fully autonomous buyer.
Build a workflow for my [type of business] that reads [Excel file] for inventory levels and customer orders, flags items below [threshold], and drafts follow-up emails to customers who haven't reordered in [number] days. Save the drafts for my review and never send them automatically. Finish when a test run produces an inventory alert list and a batch of drafted emails.
An n8n and Gemini agent receives patient chat messages, keeps context, uses clinic info from Google Sheets and responds to enquiries.
An n8n workflow has AI classify web-form jobs by type, urgency and summary, create an Airtable record, reply instantly and flag uncertain cases.
Lindy agents summarized meeting notes, sent action items to teammates, suggested knowledge-base replies on support tickets, and handled follow-up emails and calendar updates.