Synthesis of
Data Classes.
Supply Source JSON
Paste the JSON response you intend to model into the primary editor.
Select Target Language
Choose from TypeScript, Swift (Codable), Kotlin (Data Class), or C# (POCO).
Define Root Identity
Specify a name for the top-level class (e.g., "User" or "AuthResponse").
Generate Implementation
Click "Build Models" to instantly synthesize the entire class hierarchy.
Integrate & Deploy
Copy the code directly into your IDE. All nested objects are handled automatically.
Multi-Language Support
Our generator identifies nested lists and objects, creating a recursive structure that mirrors your data accurately across all major development environments.
Intelligent Naming
The engine automatically converts snake_case or kebab-case JSON keys into idiomatic CamelCase or PascalCase properties for your target language.
Nested Object Logic
Unlike simple flat generators, we extract deep nested structures and create separate, clean classes for each unique object found in the array.
Type Inference
We analyze the entire dataset to infer the most accurate types. If a field contains both integers and floats, we default to the safer Double/Float type.
Accelerating the Type-Safe Future.
In modern software engineering, manual data modeling is a bottleneck. Developers spend hours writing boilerplate code to map JSON API responses to local objects. This manual process is not only slow but also highly susceptible to "Type-O" bugs and structural mismatches.
Our JSON to Model generator automates this layer of the stack. By applying sophisticated code synthesis techniques, we turn your data into ready-to-use source code. Whether you are building an iOS app with Swift, an Android app with Kotlin, or a web frontend with TypeScript, our generator ensures your models are perfectly synced with your API's reality.
Naming & Modeling Tips
Meaningful Roots
Avoid generic names like "Data" for your root class. Use "UserProfile" or "ProductDetails" for clarity.
Handle Optionals
Remember that any key that isn't present in every JSON sample should be marked as Optional in your code.
Review Arrays
The generator uses the first element of an array to map types. Ensure your sample is representative.
Flattening
If your JSON is too deeply nested, consider flattening the payload before generating models for better UX.