​

AI Modeling

AI Modeling in AI Squared allows you to connect, configure, and prepare your hosted AI/ML models for use inside business applications. This process ensures that AI outputs are both reliable and context-aware—ready for consumption by business users within CRMs, ERPs, and custom interfaces.

​

Why AI Modeling Matters

Simply connecting a model isn’t enough—each model expects specific inputs and returns outputs in a particular format. AI Modeling provides a no-code interface to:

• Define input and output schemas
• Format and validate requests before they’re sent
• Clean and transform responses before embedding
• Map model insights directly into business apps

​

Key Benefits

• Standardization: Ensure data passed to and from models adheres to consistent formats.
• Configurability: Customize model payloads, headers, and transformations without writing code.
• Reusability: Use one model across multiple Data Apps with different UI contexts.
• Feedback-Ready: Configure outputs to support user feedback mechanisms like thumbs-up/down, scale ratings, and more.

​

What You Can Do in This Section

• Connect to an AI/ML model source (like OpenAI, SageMaker, or Vertex AI)
• Define input and output fields
• Add optional pre-processing and post-processing logic
• Test your model’s behavior with sample payloads
• Finalize your model for embedding into business workflows

AI Modeling is the foundation for building Data Apps—which surface model results in enterprise applications and enable user feedback.

Ready to configure your first model? Jump into Connecting a Model Source or learn how to define your input schema.