Palette Neat

Palette Neat is the SiMa.ai software development toolkit for building AI applications on Modalix. It includes the development environment, runtime library, model tooling, and DevKit validation workflow. Together, these components support the full development path: prepare a model, build an application, and validate the result on Modalix hardware.

Use this overview to understand the main parts of Palette Neat and choose the right setup, model preparation, or application development path.

Developer journey

If you are new to Palette Neat

There are two supported ways to develop applications with Palette Neat:

• Use the Neat SDK when you want a more performant development environment, especially if you plan to compile models, or cross-compile large scale C++ code.
• Develop directly on the DevKit when you want fewer moving parts with the development environment, especially when you are not doing model compilation work.

If you choose the SDK path, confirm your host meets the host requirements, then install the SDK. SDK installation applies compatible defaults, so you only need the Compatibility reference when you want to pin exact versions, upgrade components independently, or troubleshoot a version mismatch.

SDK-only fast path (no DevKit): install the SDK, then go straight to Compile a Model. Configure SDK, DevKit Sync, the Neat Library, and PyNeat are optional side-trips you can skip until you pair a DevKit.

Start Here

Prepare your host machine, Neat SDK, and DevKit for local development and hardware validation.

• Neat SDKUse the SDK for a high performance host-based workflow, model compilation, C++ builds, and DevKit validation.
• Neat LibraryInstall runtime and PyNeat directly when you want fewer moving parts to prototype apps on a DevKit.
• Compatibility GuideReference guide for supported version combinations.

Model Preparation

Turn trained models into deployable artifacts that run on Modalix hardware.

• Compile a ModelCompile pretrained ONNX vision models or GenAI models for Modalix.
• Use a Precompiled ModelStart quickly with a ready-to-run model artifact.
• GenAI with LLiMaCompile, test, and benchmark GenAI models on Modalix.

Build an App

Use the Neat Library to run models and compose production application pipelines.

• Hello Neat!Run your first Neat application and verify the development workflow.
• Develop AppsBuild AI applications with the Neat Library using C++ or PyNeat.
• TutorialsFollow guided examples for real Neat application patterns.

Tools & Reference

Use supporting tools and reference material when you need more detail.

• Toolssima-cli, Model Zoo and Insight.
• ReferenceBrowse APIs, troubleshooting, environment variables, data formats, and release notes.
• TroubleshootingFind fixes for setup, runtime, and pipeline issues.