10 Powerful AI Automation Use Cases for Streamlining Workflows

Introduction

In today's fast-paced digital landscape, leveraging AI automation to streamline workflows and boost productivity has become increasingly crucial. This use case explores 10 innovative AI automation solutions that harness the power of large language models (LLMs), APIs, and seamless integrations to tackle a wide range of tasks efficiently.

The LLM Split Testing use case enables users to compare responses from multiple large language models, such as ChatGPT, Claude, and Anthropic, for a given prompt. By integrating with make.com and airtable, users can submit prompts through a form, which triggers an automation that sends the prompt to various LLMs and updates the responses in an airtable database. This streamlined process eliminates the need for multiple browser instances and facilitates efficient model testing and comparison.

The PDF Extraction System automates the process of extracting key information from PDF documents. By monitoring a designated Google Drive folder, the system triggers an OCR process when a new PDF is added. It then sends the recognized text to ChatGPT, which generates a structured summary with an executive summary and key takeaways. The output is parsed and stored in an airtable database, providing users with a concise overview of lengthy or complex PDF documents.

The Zoom Call Input Automation streamlines the process of managing and organizing Zoom call recordings and transcripts. Once a Zoom call recording is processed in the cloud, the automation downloads the transcript, uploads the video to Vimeo, and creates records in an airtable database with the transcript, video link, and chat log. This automation eliminates manual intervention and saves significant time for teams or communities that conduct frequent Zoom calls.

The RSS Feed Input Automation allows users to aggregate multiple RSS feeds from various sources, such as newsletters, news articles, blogs, and YouTube videos, into a single collection. This automation monitors the aggregated feed for new content, extracts relevant information (e.g., titles, articles, and HTML content), and creates records in an airtable database. This streamlined process enables users to stay up-to-date with the latest news and information from multiple sources without manual effort.

The YouTube Transcript Extraction use case enables users to extract transcripts from YouTube videos by simply providing the video URL. By integrating with Apify actors and airtable, users can submit video URLs through a form, triggering an automation that scrapes and cleans the transcript. The cleaned transcript is then stored in an airtable database, allowing users to repurpose the content for various purposes, such as creating social media posts, structured guides, or training data for AI models.

The Deep Research Automation allows users to input ideas or topics through a form, which triggers an automation that leverages LLMs like Perplexity to conduct in-depth research and white paper creation. The resulting research is structured, named, and stored in an airtable database, providing users with a comprehensive resource for further exploration or decision-making.

The Slack Audio Transcription use case enables users to record audio messages in a designated Slack channel, which triggers an automation that transcribes the audio to text. The transcribed text is then named and stored in an airtable database, allowing users to capture and organize ideas or notes hands-free, without the need for manual transcription.

The iPhone Speech Automation allows users to capture ideas or notes using voice commands on their iPhone. By tapping a widget or invoking Siri, users can dictate their thoughts, which are then transcribed, named by ChatGPT, and stored in an airtable database. This hands-free approach streamlines the process of capturing and organizing ideas on-the-go.

The Personal Health Data Integration use case leverages wearable devices like the Oura Ring to track and monitor personal health data, such as sleep patterns, heart rate variability, and body temperature. By integrating with the device's API and Notion, this automation imports sleep statistics and readiness scores into a personal dashboard, providing users with a centralized view of their health metrics and enabling data-driven insights.

The HTTP Requests from GPT use case demonstrates how to leverage HTTP requests within GPT models to retrieve and send information from external sources, such as airtable databases. By setting up actions and schemas within the GPT model, users can pull content from their airtable records or other web services without manual copy-pasting, streamlining the workflow and enabling seamless integration of external data sources.

These 10 AI automation use cases showcase the power of leveraging LLMs, APIs, and seamless integrations to streamline workflows and boost productivity across various domains. By automating tasks such as data extraction, transcription, research, and content creation, users can save significant time and effort, enabling them to focus on higher-value activities. Implementing these solutions can lead to increased efficiency, better organization, and data-driven decision-making.