Have you ever uploaded a blog post or a product description and sat there scratching your head, trying to come up with the "perfect tags" for SEO?
Manual tagging is tedious. You read, you think, you type... then you realize you forgot a key term. Now, imagine a system where you simply paste your text, and an AI Agent instantly extracts the 3-5 most relevant keywords and saves them neatly into your database.
In this guide, we’re leveling up our no-code skills using Momen to build a Smart Tagger.
Beyond Blogging: Where Else Can This Work?
This logic isn't just for articles; it's a game-changer for any data-heavy business:
- Legal & Finance: Paste a contract or report; let the AI extract "Key Parties," "Due Dates," or "Contract Type."
- E-commerce: Feed in a product description; the AI automatically generates "Style," "Material," and "Occasion" tags.
- Education: Teachers can paste lesson plans to automatically generate "Subject Area" and "Skill Level" tags for easy searching.
- Project Management: Paste a meeting transcript; have the AI tag it with the "Department" or "Project Name" mentioned.
Step-by-Step: Turning Text into Data
To follow along with the technical details, check out the Official Documentation and the Step-by-Step Video Tutorial.
Step 1: The "Parent & Child" Setup (Data Model)
In the world of data, one article can have many tags. This is called a One-to-Many Relationship.
Table Name
Field Name
Type
Note
article
title
Text
The headline of the article.
content
Text
The main body of the article.
tag
name
Text
The keyword extracted by AI.
- Create a table for Articles (Title and Content).
- Create a table for Tags (Name).
- The Connection: Link them so that every tag "knows" which article it belongs to.
Step 2: Training the Analyst (AI Agent)
We create an AI Agent named agent_smart_tagging.
- We tell it: "You are a professional Content Assistant. Your goal is to extract 3-5 core keywords. Ignore the fluff."
- Set the output to Structured and tell the AI to return an Array (a list) of strings. This allows our app to handle each tag individually.
Step 3: The "Magic Loop" (Actionflow)
This is where the magic happens. Since the AI is giving us a list of tags, we need a workflow that handles them one by one.
- AI Node: Analyzes the title and content.
- Save Article: Saves the main text first.
The Loop: This node looks at the AI's list. For each tag the AI found, it runs an "Insert" command into the Tag table.
Pro Tip: This ensures that whether the AI finds 3 tags or 5, your database handles it perfectly every time!
Step 4: The One-Click UI
Drag two text inputs onto your page (one for the title, one for the body) and add a "Get Started" button. Bind the button to your Actionflow. Now, when you click, the app talks to the AI, saves the article, and loops through the tags—all in a split second.
Put it to the Test!
Open your Preview Mode and paste a news article.
Hit "Get Started."
When you peek into your database, you’ll see your article in one table and the AI-generated tags in the other, perfectly linked and ready for your website!
Ready to build? You can play with the finished project template here: Project Access Link.
With tools like Momen, if you can imagine the logic, you can build the solution.
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