Generate AI avatar videos with HeyGen and Google Sheets integration

Watch and filter rows in Google Sheets to add new entries automatically

Automatically monitor Google Sheets for new rows, filter them based on criteria, and add new entries seamlessly. Ideal for dynamic data management.

Automated sales follow-up system using HighLevel, Gmail, Slack & Google Sheets

Description: This workflow automates sales contact follow-ups and engagement tracking by integrating HighLevel CRM, Gmail, Slack, and Google Sheets. It fetches all contacts from HighLevel, filters inactive contacts, sends personalized follow-up emails, checks for responses, and notifies the sales team accordingly. It eliminates manual follow-up tracking, ensures timely outreach, and provides real-time notifications — helping sales teams maintain engagement, respond promptly, and improve le

Keep track of every Olark visitor in Google Sheets

Every time a new Olark conversation is started, Make will automatically save the visitor's information in Google Sheets. The template uses this [example spreadsheet](https://docs.google.com/spreadsheets/d/1LDyuXsIyH1hoPM2XdHGhp8KCoYDiZ-FWoFBRjuOLqXw/edit?usp=sharing).

Generate responses using Perplexity AI and ChatGPT from Google Sheets range values

Automatically generate responses using Perplexity AI and ChatGPT and update Google Sheets. Fetch sheet range values, create chat completions, and update rows efficiently.

Add new Facebook Lead Ads leads to Google Sheets for easy tracking

Automatically track new Facebook Lead Ads leads by adding their details to Google Sheets, ensuring organized and accessible lead management.

Personalize an introduction message with ChatGPT for new Salesforce leads and store them on a Google Sheet for review

Optimize your lead nurturing with personalized introduction messages for new Salesforce leads, conveniently organized and stored in Google Sheets for easy review before emailing.

Compare sequential, agent-based, and parallel LLM processing with Claude 3.7

This workflow demonstrates three distinct approaches to chaining LLM operations using Claude 3.7 Sonnet. Connect to any section to experience the differences in implementation, performance, and capabilities. What you'll find: 1️⃣ Naive Sequential Chaining The simplest but least efficient approach - connecting LLM nodes in a direct sequence. Easy to set up for beginners but becomes unwieldy and slow as your chain grows. 2️⃣ Agent-Based Processing with Memory Process a list of instructions through

Extract text from PDF and image using Vertex AI (Gemini) into CSV

Case Study I'm too lazy to record every transaction for my expense tracking. Since all my expenses are digital, I just extract the transactions from bank PDF statements and screenshots into CSV to import into my budgeting software. Click here to watch Youtube tutorial What this workflow does - Upload your PDF or screenshots into Google Drive - It then passes the PDF/image to Vertex Gemini to do some A.I. image recognition - It then sends the transactions as CSV and stores it into another Google