How to Build an AI Cat Digestive Analysis Tool with Momen

Introduction: How AI can help pet owners to monitor cat health

Your cat can’t explain how they feel — but their poop can reveal a lot. Sometimes you might notice something unusual in the litter box, but it’s hard to know:

• Should I be concerned?

• Is this normal?

• Do I need to call the vet?

That’s where AI comes in — helping you make sense of what you see, avoid unnecessary panic, and even offering professional, data-backed suggestions.

In this tutorial, we’ll show you how to build your own AI cat health analysis tool using Momen, a no-code platform. Step by step, you’ll learn how to use AI agents, conditional views, and smart UI logic to create a tool that analyzes cat poop photos for health insights.

👇 Try the working demo below:

Key Component: Conditional Views

Before building, let’s understand one key UI element: Conditional Views. These allow your app to display different screens or messages based on the app’s state — like when the user uploads an image, the app is analyzing, or the result is ready.

In our project, we’ll switch between:

• 📷 Input view (image upload)

• ⏳ Loading screen

• ✅ Result view

Step-by-Step Guide to Building an AI Cat Poop Detector

Step 1: Designing the UI

Your app will consist of three main views:

Input View (Image Upload)

• Use the Image Picker component to let users upload a photo (limit to one image).

• Add instruction text and style it as needed.

• Include a "Check My Cat’s Health" button.

• This button will later be wired to trigger the AI agent and start the analysis.

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📊 Generated View (Analysis Results)

This screen displays the AI-generated insights, including:

• A health status banner (e.g., healthy, needs attention, urgent)

• A diagnosis summary based on the image

• Personalized care tips

• Two static text blocks:

  • A medical disclaimer

  • Friendly reminder or helpful advice

We’ll focus on the first three since they require data binding from the AI response.

• The status banner uses a Conditional View, changing its message and color based on the AI output (stored in a page variable).

• The diagnosis and tips sections display AI-generated text bound to variables as well.

Step 2: Configuring AI agents

Now to the heart of the tool — the AI agents.

We use two AI agents in this project:

🧠 tools_cat Agent – The Analyzer

• This agent is responsible for analyzing the uploaded cat poop image.

• It uses Gemini 2.5 (Google’s advanced language model) to reason based on visual input.

• Rather than fine-tuning the model, we implement RAG (Retrieval-Augmented Generation) — meaning the agent pulls from a veterinary-informed document base every time it runs.

• This ensures consistent, professional-quality answers rooted in real medical knowledge.

🏷️ keywords_extractor Agent – The Assistant

• This agent scans the uploaded image and extracts relevant keywords (e.g., “runny,” “dark,” “mucus”).

• These keywords help guide the tools_cat agent to search more accurately within the knowledge base.

Step 3: Connecting the Logic with Actionflow

To pass data between agents, we use Momen’s Actionflow.

Here’s how it works:

• Chain both agents together in a workflow.

• The first input is the image.

• The output of keywords_extractor becomes input metadata for tools_cat.

• The final result remains structured, so it’s easy to bind directly to UI elements.

Step 4: Binding the Frontend

Now we bring it all together on the front end:

• The "Check My Cat’s Health" button triggers the Actionflow.

• On success, we store the AI result into three page variables:

  • status

  • result

  • tips

• The Conditional View switches based on whether those variables are null, giving the user the right experience at the right time.

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Final Thoughts

With just a few components and powerful AI, you've now created a no-code pet health analyzer that feels intelligent, empathetic, and useful. You’ve also learned how to:

• Work with Gemini 2.5

• Integrate RAG-based AI agents

• Build real-time, responsive views with data binding

Ready to build your own?
Try Momen, a no-code platform for launching custom AI-powered tools and automations—no coding skills required.
Perfect for pet startups, DIY devs, or anyone who wants to build smarter tools faster.