Hanzo ML

Interactive development environments with GPU support. Collaborate in real-time, version everything.

Build and run reproducible ML pipelines. DAG-based workflow orchestration with artifact tracking.

Train models at scale with PyTorch, TensorFlow, XGBoost. Distributed training made simple.

AutoML and hyperparameter search with Katib. Find the best model configuration automatically.

Deploy models to production with KServe. Auto-scaling, canary deployments, A/B testing.

Complete foundation model ecosystem from edge to cloud. Language, vision, 3D, video, and audio generation in a unified family.

Mixture of Unbound Experts with Noise (MUEN) architecture. Unifies understanding and generation across text, vision, and audio through diffusion.

Next-generation 17B parameter image foundation model. Achieves state-of-the-art quality within seconds.

Blazingly fast end-to-end song generation with latent diffusion. Create complete songs with vocals and accompaniment.

Video generation in latent space with explicit temporal dynamics. High-quality frame coherence with reduced compute.

Multimodal language model unifying text, vision, audio, and 3D.

Track model versions, artifacts, and lineage. Approval workflows and provenance tracking.

Manage ML features with Feast. Offline features in warehouse, online in KV for low-latency serving.

Evaluate models in production. Benchmarks, drift detection, and quality monitoring.