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Founded Year

2021

Mosaic Score
The Mosaic Score is an algorithm that measures the overall financial health and market potential of private companies.

-26 points in the past 30 days

About Make

Make is a company that focuses on automation software, operating within the technology and software industry. The company offers a visual platform that allows users to design, build, and automate tasks, workflows, apps, and systems without the need for coding. Its services are primarily utilized by individuals, teams, and enterprises across various sectors. It was founded in 2021 and is based in Prague, Czech Republic.

Headquarters Location

Menclova 2538/2

Prague, 180 00,

Czech Republic

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ESPs containing Make

The ESP matrix leverages data and analyst insight to identify and rank leading companies in a given technology landscape.

EXECUTION STRENGTH ➡MARKET STRENGTH ➡LEADERHIGHFLIEROUTPERFORMERCHALLENGER
Enterprise Tech / Enterprise Applications

The business process automation (BPA) market refers to the market that offers software and services to automate and streamline repetitive and manual tasks within organizations. It involves the use of technology, such as robotic process automation (RPA), artificial intelligence (AI), and workflow management systems, to optimize business processes and improve efficiency. BPA encompasses a wide range…

Make named as Challenger among 15 other companies, including IBM, UiPath, and Cisco.

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Latest Make News

How to use ChatGPT to automate tasks using GPT actions

Sep 11, 2024

Geeky Gadgets 1:14 pm Automating tasks using ChatGPT can transform your productivity by seamlessly integrating it with a wide range of external applications. This guide will walk you through the process of setting up these automations, including creating a custom GPT, configuring webhooks, and using the powerful Make automation platform. By following these steps, you can unlock the full potential of ChatGPT and streamline your workflow like never before. TL;DR Key Takeaways : Automating tasks with ChatGPT can boost productivity by integrating with external applications. Create a custom GPT by naming it, adding a description, profile picture, and setting up instructions. Understand GET (retrieve information) and POST (send information) requests for setting up automations. Use Make to set up webhooks and create automation scenarios for various applications. Create JSON schemas with Schema Ninja GPT for dynamic data mapping to webhooks. Test and refine your GET and POST requests to ensure proper data flow and functionality. Example: Automate LinkedIn posts from aggregated news articles using filters and routers in Make. Finalize and use the automation to save time and increase productivity. Join the AI Foundations Community for additional resources and advanced AI automation techniques. Automating tasks using ChatGPT can transform your productivity by seamlessly integrating it with a wide range of external applications. This comprehensive guide will walk you through the process of setting up these automations, including creating a custom GPT, configuring webhooks, and using the powerful Make platform. By following these steps, you can unlock the full potential of ChatGPT and streamline your workflow like never before. Harnessing the Power of Custom GPTs The first step in automating tasks with ChatGPT is to create a custom GPT tailored to your specific needs. This process involves: Naming your GPT: Choose a descriptive and memorable name for your custom GPT. Providing a description: Clearly outline the purpose and functionality of your GPT. Adding a profile picture: Personalize your GPT with a relevant and engaging image. Setting up instructions and conversation starters: Define how your GPT will interact with users and initiate conversations. For example, if you want to automate LinkedIn posts by aggregating news guides, you can create a custom GPT specifically designed for this purpose. By carefully crafting your GPT’s instructions and conversation starters, you can ensure that it effectively gathers and processes the necessary information. ChatGPT Automation is Using GPT Actions Mastering GET and POST Requests To successfully set up your ChatGPT automations, it’s crucial to understand the difference between GET and POST requests: GET requests: These requests are used to retrieve information from a specified resource. POST requests: These requests are used to send data to a server to create or update a resource. For instance, you can use a GET request to fetch data from a Google Sheet containing relevant information for your automation. On the other hand, a POST request can be used to send the processed data to an email service or a social media platform like LinkedIn. Unleashing the Power of Make Make is a innovative automation platform that enables you to set up webhooks and create intricate scenarios for a wide range of applications. With Make, you can create modules for various services, such as: Google Sheets: Integrate data from spreadsheets seamlessly into your automations. RSS feeds: Aggregate news guides and blog posts from multiple sources. Social media platforms: Automate posts, updates, and interactions on platforms like LinkedIn, Twitter, and Facebook. By using the power of Make, you can create sophisticated automations that save you time and effort. For example, you can set up a scenario that automatically aggregates news guides from RSS feeds, processes the data, and creates engaging LinkedIn posts without any manual intervention. Streamlining Data Flow with Schema Creation and Integration To ensure a smooth and dynamic data flow between applications, you can use Schema Ninja GPT to create JSON schemas for your GET and POST requests. These schemas act as a blueprint for your data, defining its structure and format. By mapping data dynamically to webhooks using these schemas, you can guarantee that the information is transferred accurately and efficiently between different services. Ensuring Success with Testing and Refinement Before deploying your ChatGPT automations, it’s essential to thoroughly test your GET and POST requests. This testing process will help you identify any potential issues or bottlenecks in your data flow. Based on the results of your tests, you may need to refine your instructions, schemas, or scenarios to ensure optimal performance. By iteratively testing and refining your automations, you can guarantee that they work flawlessly and deliver the desired results. Putting It All Together: A Practical Example Let’s walk through a practical example of automating LinkedIn posts using aggregated news guides: Set up filters and routers in Make: Configure Make to handle different types of requests and route them to the appropriate modules. Create modules for data aggregation: Set up modules to fetch news guides from RSS feeds and store them in a structured format. Process and format the data: Use ChatGPT to process the aggregated guides, extract relevant information, and format it for LinkedIn posts. Automate post creation and publishing: Configure a module in Make to create and publish LinkedIn posts using the processed data from ChatGPT. Test and refine the automation: Thoroughly test the entire automation process, from data aggregation to post publishing, and make any necessary adjustments to ensure smooth operation. By following these steps, you can create a powerful automation that saves you time and effort while consistently delivering high-quality content to your LinkedIn audience. Reaping the Benefits of ChatGPT Automation Once your ChatGPT automation is set up and tested, you can start reaping the benefits of increased productivity and efficiency. With tasks like data aggregation, content creation, and social media posting handled automatically, you can focus on more strategic and high-value activities. As you continue to use and refine your automations, you’ll discover new ways to streamline your workflow and achieve even greater results. Expanding Your Automation Horizons To further enhance your ChatGPT automation skills and knowledge, consider joining the AI Foundations Community. This vibrant community offers a wealth of resources, tutorials, and support from experienced automation enthusiasts. By engaging with the community, you can learn advanced techniques, discover new use cases, and stay up-to-date with the latest developments in AI-powered automation. By following the steps outlined in this guide and using the power of ChatGPT, Make , and Schema Ninja GPT, you can create sophisticated automations that transform your productivity. Whether you’re automating social media posts, data analysis, or any other task, the possibilities are endless. Embrace the future of work and start automating your way to success today!

Make Frequently Asked Questions (FAQ)

  • When was Make founded?

    Make was founded in 2021.

  • Where is Make's headquarters?

    Make's headquarters is located at Menclova 2538/2, Prague.

  • Who are Make's competitors?

    Competitors of Make include doFlo, Keragon, Drafter AI, Hubler, Sheetgo and 7 more.

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Compare Make to Competitors

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Zapier

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Kissflow

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IFTTT

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Tray

Tray is an AI-powered integration platform as a service (iPaaS) that specializes in business process automation and data integration. The company offers a composable AI integration platform that enables rapid development and deployment of automated workflows and data integrations, with a focus on low-code solutions that cater to both technical and non-technical users. Tray's platform is designed to facilitate digital transformation and streamline enterprise technology stacks, with an emphasis on increasing execution velocity and simplifying complex processes. It was founded in 2012 and is based in San Francisco, California.

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Workato

Workato specializes in artificial intelligence (AI) powered enterprise automation. The company offers a platform that enables businesses to automate their processes by integrating their applications, data, and experiences, all in a low-code, no-code environment, primarily serving sectors such as information technology, human resources, sales, marketing, finance, and support. It was founded in 2013 and is based in Mountain View, California.

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Quickbase

Quickbase operates as a company that focuses on providing a work and project management platform. The company offers a no-code platform that allows users to create, connect, and customize applications, facilitating project management, compliance management, resource management, and workflow management among other functions. Quickbase primarily serves sectors such as construction, solar, manufacturing, government, and retail. Quickbase was formerly known as OneBase. It was founded in 1999 and is based in Boston, Massachusetts.

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