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.
A professor had an agent regrade TA-graded assignments, verify answers with Claude, and revise grades and feedback in Brightspace, catching missed issues.
A professor had an agent regrade TA-graded assignments, verify answers with Claude, and revise grades and feedback in Brightspace, catching missed issues.
The professor gave the already TA-graded assignment submissions to OpenAI's agent. The agent regraded every submission to find issues the TA missed, verified AI-generated answers by querying Claude, and directly revised all grades and feedback inside Brightspace. The professor only initiated the request.
The process produced expanded feedback and adjusted grades that caught additional problems the TA had overlooked. The professor reached a new level of confidence in the AI output.
Take the submitted assignments in [folder or export] for [course name] along with the answer key and rubric in [file]. Regrade each one, verify the correct answers independently, and produce a table of any grade changes with the reason and proposed feedback text. Do not update the grades in [Brightspace or my LMS] until I have reviewed the table and approved it.
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.