Triggered by a new row in Google Sheets, this workflow sends lead data to an AI for qualification based on predefined rules. The AI evaluates the lead, and its response is then processed to extract the qualification status. Finally, the original Google Sheet row is updated with the lead's qualification (qualified or not qualified).
This workflow is triggered when a new row is added to a Google Sheet containing a document link. It processes the document (e.g., a PDF resume) by extracting its text content. Using prompts fetched from another Google Sheet, an AI extracts specific fields of information. Finally, the extracted data is updated back into the original Google Sheet row.
This workflow monitors a Google Sheet for new customer feedback submissions. It then uses Gemini AI to analyze the feedback, extracting emotionally engaging and impactful testimonial quotes. Finally, the extracted testimonials are automatically added to a "Testimony" column in the Google Sheet, and an email notification is sent to the marketing team.
This workflow triggers when a new row is added to a Google Sheet containing a company website URL. It then scrapes the content from that website, uses an AI model to extract key company information such as market, industry, target audience, and value proposition. Finally, the workflow updates the original Google Sheet row with this enriched data.
This workflow collects article details via a form (e.g., Google Forms). It then uses AI to generate an article outline and the full article content based on the inputs. Finally, it saves the generated content to Google Drive and updates a Google Sheet with links for tracking article progress.
This workflow automatically detects new customer feedback submitted via Google Forms (by monitoring a Google Sheet). It then uses AI to analyze the feedback content and extract impactful testimonial quotes. The extracted quotes are saved to a Google Sheet database, and an email notification is sent to the marketing team with the new testimonial.
This workflow automatically generates detailed product comparison content. It can be triggered manually or when a new row is added to Google Sheets, taking two product names as input. An AI model then generates a compelling title, a feature-by-feature comparison, use-case recommendations, and an FAQ section. Finally, the generated content is saved into a Google Sheet for review or publishing.