Unit Introduction
Welcome to Get started with AI in Make, the first unit of the course!
In the previous courses, you have learned the basics of AI, LLMs, and GenAI. Now it is time to use AI in Make. In this unit, you will learn:
You will learn: why you should include AI in your scenarios
which AI tools are available in Make
some practical use case examples
AI and Make
You might be wondering why you should use AI in Make and what are the benefits? The answer is simple: both AI and Make help each other.
AI makes it easier to handle unorganized data, while Make connects different systems so that everything works together.
This combination helps you create better and more efficient workflows. Let’s go on to learn more about how AI and Make work together.
What AI brings to Make
Unstructured data is every analyst’s nightmare. It is data that doesn’t have a
predefined structure and can come in many forms, such as text documents, images, or videos.
Analyzing unstructured data often requires manual intervention to organize and
extract useful information.
Using unstructured data in a scenario can be quite complex, but AI can help by analyzing and organizing it. AI can interpret text, images, or other complex formats, making it possible to include tasks like detecting emotions in text, recognizing images, or understanding human language in Make scenario workflows.
Eric the Engineer is trying to calculate the distance between two stars, but the data is all mixed up: nebulae, comets, and planets are all mixed together. Frustrated, he asks Alicia the Astronomer for help. Alicia organizes the data, highlighting the important points, so Eric can complete the calculation easily.
What Make brings to AI
AI looks at data from different sources, like customer feedback, sales records, and social media, to find patterns and make predictions.
For example, AI can analyze customer sentiment to predict trends or spot areas for improvement. But on its own, AI would need manual help to act on these insights, like updating customer details or sharing reports.
That’s where Make comes in.
Make connects different systems and tools, making it easy to link AI results with actions, like updating a database or sending an email.
Alicia the Astronomer wants to track the movement of a newly discovered comet, but the data is coming from different telescopes, satellites, and observation points, all in separate systems. She struggles to get everything in one place, so Eric the Engineer uses automation to connect all the data sources. Alicia can now study the new comet easily, getting solid evidence for her new scientific paper.
AI provider
You’ve seen that by combining AI and Make you can reach the stars. Within Make, you can easily add AI to your scenarios.
You might be wondering, how can I practically use AI capabilities? That’s where AI providers come in. AI providers are external companies that provide access to AI services. You need to connect to an AI provider to get access to a Large Language Model (LLM), which allows it to understand and generate text.
In Make, you can choose between two types of AI provider connections:
External AI providers: You can use your own connection to an existing account with an external AI provider, like OpenAI or Anthropic Claude. This option is available to users on Pro, Teams, or Enterprise plans.
Make’s AI Provider: You can add a connection without subscribing to a third party service or create an account. Make handles the connection to an AI provider for you. This is available to users on all plans.
Each AI provider offers access to different LLMs. The results will vary based on the model you select. Choosing the right model depends on the type of task and the results you want to achieve. You will learn more about choosing the right model later.
AI modules
You might be wondering, how can I add AI to my Make scenarios?
In Make, there are two main ways in which you can add AI to your scenarios: using Make’s own AI apps or using one of the third-party AI provider apps. You can decide which works best for your workflows.
MAKE AI APPS THIRD PARTY AI PROVIDER APPS
They are Make built-in AI apps that allow you to perform specific actions. Using these apps means setup is easier. Modules are ready to use and you can use Make’s AI provider, with no need for external accounts. This makes them a quick, low maintenance way to add AI to your scenarios. You also have the option to connect to external AI providers if you are on the Pro plan or higher.
Make AI apps are built for tasks like summarizing, extracting information, or reformatting content. You don’t need to modify prompts, as they come pre-set for common use cases. These apps include Make AI Toolkit and Make AI Content Extractor. You will learn more about these specific apps in the next unit of the course.
MAKE AI APPS THIRD PARTY AI PROVIDER APPS
You can connect to third-party applications to include AI services in your scenario. As you learned in the previous course, Make uses APIs to connect to these tools, making their functionalities available for your use cases. To use these apps, you need to create an account with the third-party AI provider so you can connect it with Make.
Each of these apps in Make represents an AI provider and each module is a specific function of that service. Some of these apps, like Eden AI, also include ready-to-use modules so you can quickly add AI to your scenarios without writing a prompt.
Here you can find a list of AI services you can include in your scenarios. Make always updates the list to include the new services and functionalities that are developed. This is especially useful for scenarios that require specific actions or greater customization. You can explore them to find the apps that match your needs.
Here are some examples of scenarios that you can implement while using AI in Make. While these focus on marketing and sales, you can easily adapt them for other purposes. The sky is the limit here.
Personalized email replies
AI extracts customer data and writes a personalized reply when a new email arrives.
Chatbot workflow integration
AI provides a personalized response when it receives messages from a customer in the chat.
Lead scoring automation
AI rates potential customers (leads) based on their likelihood to make a purchase.
Lead segmentation
AI categorizes potential customers (leads) based on specific criteria.
Churn risk analysis
AI calculates the risk of losing a customer. Anomaly detection
AI detects inconsistencies in customer data, like duplicates or missing fields.
Example use cases
Quite cool what you can do with Make and AI, right?
Let’s look at some other examples by exploring some use cases in more detail. Take a look at the different AI tools present in each scenario. They’ll give you an idea of the different tasks that AI can perform that you can
include in your scenario. In these cases, we will use third-party applications, but you could perform some of the same actions using Make AI apps.
1: Sentiment analysis
Sentiment analysis
Maria the Marketing Manager of Space Oddities Tech, wants to detect the sentiment of the emails she receives from her customers. For negative emails, she wants to create a task in Trello for a follow-up. For all emails, she wants to classify them by content (for example: complaint, congratulations, suggestion, etc) and send the email content along with the
sentiment to the relevant Slack channel.
Eden AI> Identify general sentiment of a text to detect the sentiment of the email.
OpenAI> Message an assistant to classify the email based on its content.
2: Image categorization
Image categorization In her free time, Maria runs an amateur photography group.
The users upload their images to a shared drive and Maria would like to analyze the content of every image, categorize each one, and rename each file accordingly. She also wants to save the results to a spreadsheet.
Groq> Analyze Images to get more information about the content of the image.
Mistral> Create a Chat Completion to categorize the images based on their content.
3: Auto translation
Auto translation
Maria manages a Telegram chatbot that receives messages from customers worldwide.
She wants to detect the language of the message, generate a reply in the same language, and send it back to the chatbot. She also wants to translate the message into English for herself and her team, and share the translated version in the customer service channel in Slack.
Eden AI> Detect Language of Text to detect the language of the message.
Claude> Create a Prompt to generate an answer using the customer’s language.
DeepL> Translate a Text to translate the message into English.
Automatic replies
Maria manages her company’s Instagram account. Whenever someone comments on one of their posts, she wants to automatically
generate and add a reply to the comment. She has strict guidelines for the tone, language and content to reduce the risk of inappropriate replies.
Open AI> Message an Assistant to generate a reply to the post comment taking into account the guidelines Maria provides,
Continuetothewrapupforthisunit
Wrap up
AI helps Make handle unstructured data by analyzing and extracting valuable insights from text, images and other non-organized information,
making it easier to work with data that doesn’t fit into traditional tables or databases.
Make connects different sources, such as APIs, databases, and other tools, allowing AI to access and integrate data from multiple platforms and systems.
You can use Make owned AI apps to easily add AI capabilities into your scenarios. They are built for everyday text tasks like summarizing, extracting, or reformatting content.
Unit complete
Great job! You have completed the first unit of the Using AI in Make course.
By now you should have an understanding of:
Why you should include AI in your scenarios
Which AI tools are available in Make
Some practical use cases Move on to the next unit, you will explore two Make AI apps.
Mark this task complete to continue to the next unit.