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.
@dani_avila7 tested Perplexity Computer on multiple tasks, where it picked Gemini 3 Flash for some steps and Opus 4.6 for code writing.
@dani_avila7 tested Perplexity Computer on multiple tasks, where it picked Gemini 3 Flash for some steps and Opus 4.6 for code writing.
User started the Perplexity Computer agent and let it run autonomously until tasks finished. The agent selected models per step on its own, using Gemini 3 Flash for several tasks before switching to Opus 4.6 for code writing.
It completed the observed tasks via automatic model routing.
I want you to complete this multi-step task: [describe the goal, e.g. research competitors, write a script to analyze the data, and produce a summary report]. Break it into steps, use whichever tools and models fit each step best, and tell me at the end which approach you used for each one. You're done when you've delivered [specific output, e.g. a report file and the script]. Pause before sending anything externally or spending money.
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.