Quick overview Automatically read inbound email replies, use AI to detect intent and sentiment, and send natural in-thread responses. Opt-out requests are confirmed, pushed to your ESP suppression list, and logged. A hands-off reply layer that keeps your sender reputation clean while every conversation gets fast, human-sounding answer. How it works An IMAP trigger watches your inbox and picks up new reply emails as they arrive. A filter keeps only genuine replies, and a code node strips quoted history and signatures, then parses the sender name, email, and threading headers. A code node builds a strict AI prompt with the cleaned message and your trigger-word hints. The OpenAI node classifies intent and sentiment and drafts a reply, returning strict JSON. A code node normalizes the response, enforces a clean email structure, and adds your CTA once. A switch routes on the unsubscribe flag: normal replies go back in-thread through Gmail, opt-outs get a neutral confirmation. Opt-outs are posted to your ESP suppression list, every action is logged to a data table, and Gmail labels are updated to mark the thread handled.
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WSend Calendly meeting prep briefs with Gmail, Notion, OpenAI and Sheets
Quick Overview This workflow monitors Gmail for Calendly “New Event” emails, extracts meeting details with OpenAI, enriches the invitee with Notion CRM data, Google Sheets STR records, and SerpApi building research, then generates and schedules a meeting-prep brief email to send 30 minutes before the meeting. How it works Triggers every minute when a new Gmail message arrives and continues only if it is a Calendly notification for a new event. Uses OpenAI to extract the invitee email and meeting date/time from the email and calculates a send time 30 minutes before the meeting. Looks up the lead in a Notion database by invitee email and pulls building research via SerpApi, then uses OpenAI to extract building details from the AI Overview results. Loads STR registration data from Google Sheets and matches it to the building address to flag whether the property appears in STR records. Searches recent Gmail history in two accounts for messages involving the lead’s email address and checks whether any history exists. If email history exists, uses OpenAI to summarize the relationship and generate a concise meeting brief, then formats it as an HTML email. If no email history exists, uses
Triage supplier capacity risk with Groq, Gmail, Slack, and Google Sheets
Quick overview This workflow runs daily to pull supplier performance data from an HTTP endpoint, calculate fulfillment and delay risk metrics, use Groq (Llama 3.3) to classify supplier risk and generate mitigation actions, then notify via Gmail and Slack and log outcomes to Google Sheets. How it works Runs every day at the scheduled time. Fetches supplier performance data from an HTTP API and stops if the supplier has no orders. Normalizes the supplier fields and calculates fulfillment rate, delay, rule-based flags, and a risk score. Sends the metrics to Groq (Llama 3.3) to classify risk (Low/Medium/High) with a reason and confidence, then merges the AI result with the computed metrics (falling back to the rule-based classification if parsing fails). If the AI risk is Medium, Groq generates three mitigation actions and the workflow fetches backup supplier options from an HTTP API, then combines both into a single alert payload. Sends the mitigation actions by Gmail email and Slack message, then appends a “high risk” audit row to Google Sheets. If the AI risk is not Medium, appends a “no alert sent” audit row to Google Sheets with the assessed risk details. Setup Add Groq API creden
Analyze YouTube comments with OpenAI, Google Sheets, and Gmail
Quick overview This workflow monitors a Google Sheets list of YouTube video IDs, fetches video details and top comments from the YouTube Data API, analyzes the comments with OpenAI into structured sentiment and themes, emails an HTML report via Gmail, and writes the results back to Google Sheets. How it works Triggers every minute when a row in Google Sheets is added or updated. Reads the video ID and status from the row and continues only if the status is set to “Pending”. Calls the YouTube Data API to fetch the video’s metadata and the top comment threads for that video. Flattens the comment threads, calculates basic stats (comment count and average likes), and compiles a limited comment text block for analysis. If comments exist, sends the compiled comments and video title to OpenAI to generate a structured analysis (sentiment score, sentiment breakdown, themes, questions, feedback, insights, and summary). Builds an HTML email report from the structured results, sends it to the configured recipient with Gmail, and updates the Google Sheet row with the analysis fields; if no comments exist, marks the row as “No comments”. Setup Create or duplicate a Google Sheet with at least “Vi