This workflow is triggered when a new page (row) is added to a Notion database. It automatically scrapes content from a specified URL on that page, uses an AI model to generate a summary and relevant tags, and then updates the original Notion page with the AI-generated summary and tags.
This workflow automatically summarizes new comments added to a Notion database page using AI. When a page in a specified Notion database is updated with new comments, the workflow extracts these comments, sends them to an AI model for summarization, and then updates a designated property on that same Notion page with the generated summary.
This workflow is triggered when a new message is received in a chat platform. It uses AI to identify if the message contains a URL and a request to save an article. If a valid article URL is found, the workflow scrapes the website's content, summarizes it with AI, and then creates a new page in a Notion database. The Notion page includes the original URL, the AI-generated summary, and other extracted metadata. Finally, a confirmation message is sent back to the chat.
This workflow is triggered when user feedback is updated in a Notion database. It uses an AI to perform sentiment analysis (Positive, Neutral, Negative) and determine if the feedback matches an existing insight or requires a new one. The workflow then updates the Notion database, linking feedback to insights and marking it as processed.
This workflow transforms a simple user query into comprehensive, well-structured HTML content. It leverages Perplexity AI for in-depth research, then uses an LLM (such as GPT) to organize the findings and generate a professional blog post in HTML format, complete with proper semantic structure and formatting.
This workflow enables users to input a research query and automatically receive a comprehensive, AI-generated report. It utilizes an AI search engine to gather information and an LLM to synthesize and format the data into a well-structured document, ready for review.
This workflow is manually triggered by providing a brand URL. It then uses GenFuse's scraping capabilities to extract content from that URL. The extracted content is sent to an AI model (like Google Gemini) for summarization and sentiment analysis, providing insights into brand perception. The final analyzed content can then be displayed or sent to another app.