Substack posts as clean text for AI and LLM pipelines
Sourabh Kumar
To feed a Substack newsletter to an AI model, set Content format to text. This example returns the 100 newest Astral Codex Ten posts as clean plain text, one row per post with title, date, word count and engagement, ready for retrieval, summaries or topic analysis.
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The Substack Scraper: Posts, Comments & Notes Actor is ready to run with the inputs already set for "Substack posts as clean text for AI and LLM pipelines". Sign up or log in and you'll land in Apify Console with a copy of this exact task.
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The Substack Scraper: Posts, Comments & Notes Actor will start running based on the input automatically. You can also change all the input fields, like newsletter, post or profile links, max posts per newsletter, and more, to match your specific use case.
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Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as title, author, published, and more.
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The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Substack posts as clean text for AI and LLM pipelines" task via API.
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