Normalization

Standardize inputs and outputs across different AI models for consistent behavior.

Overview

Normalization is the process of standardizing inputs and outputs across different AI models to ensure consistent behavior regardless of the underlying model provider. This is essential for creating reliable AI applications that can work with multiple models or switch between models seamlessly.

Key Features

• Input Formatting: Standardize prompts, parameters, and other inputs to ensure compatibility across different models.
• Output Standardization: Transform model outputs into consistent formats for easier integration with your applications.
• Cross-Model Compatibility: Create abstraction layers that allow your application to work with multiple AI models interchangeably.
• Custom Transformations: Define custom transformation pipelines for specialized use cases and domain-specific applications.

Benefits

• Reduce development time by standardizing model interfaces
• Improve reliability by ensuring consistent behavior
• Enable easy model switching and A/B testing
• Simplify integration with downstream applications

Getting Started

To start using Centrify's normalization features, navigate to the Normalization section in your project dashboard. From there, you can create normalization rules for your inputs and outputs, and apply them to your model deployments.