smile

# Statistical Machine Intelligence & Learning Engine <img align="left" width="40" src="/studio/src/main/resources/smile/studio/images/smile.png" alt="SMILE">
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SMILE (**Statistical Machine Intelligence & Learning Engine**) is a comprehensive,
high-performance machine learning and AI platform for the JVM. Built on **Java 25**
with idiomatic APIs for **Kotlin** and **Scala** (v4.x supports Java 21; earlier
versions support Java 8), SMILE covers the entire lifecycle of machine intelligence:
building models with agentic AutoML, embedding algorithms directly in your
application, and serving classical ML, ONNX graphs, and LLMs on your own machines.

### Vision: Intelligence Where the Work Is

A decision should not require a cloud round-trip or a fragile bridge to an external
Python stack. The score, the explanation, and the model update belong on the machine
that already holds the facts: inside a JVM microservice, a branch server, a payment
terminal, a vehicle gateway, or an air-gapped node. SMILE makes real-time,
autonomous machine intelligence native to the systems enterprises already run, from
resource-constrained edge gateways to multi-GPU clusters.

### What We Value

- **Sovereign & Self-Hosted by Default:** Your data, models, API keys, and telemetry stay on your machines and your network. Everything is built to run locally and keep working when the external link is down.
- **Zero-Bloat Craftsmanship:** The core engine is pure, self-contained JVM bytecode built on compact, cache-friendly data structures. You get deterministic low latency and a tiny memory footprint by default, with optional plug-and-play native acceleration (OpenBLAS/LAPACK, ONNX Runtime, LibTorch/CUDA) when hardware is available.
- **Explainable & Auditable in Place:** High-stakes decisions cannot be black boxes. SMILE provides both exact **TreeSHAP** for tree ensembles and model-agnostic **KernelSHAP** for any classifier or regressor, computing local feature attributions in-process alongside predictions, while AutoML workflows generate readable Java, Scala, Kotlin, or Python notebooks you can inspect line by line.
- **Open Source with Enterprise Backing:** Open-source licensing supports academic research and community collaboration, while commercial licensing from [HALO.AI](https://www.aihalo.dev/) removes copyleft and source-disclosure obligations for proprietary, embedded, and mission-critical production deployments.

### Key Strengths

- **Comprehensive Breadth in One Engine:** Hundreds of algorithms spanning classification, regression,