MLOps Tools

Higgsfield is a fault-tolerant, highly scalable GPU orchestration platform and machine learning framework. It solves the immense complexity of training and deploying models with billions to trillions of parameters across large, distributed clusters. It is designed for AI researchers, engineers, and organizations pushing the boundaries of large-scale model training who need robust, production-ready infrastructure.

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SIE is an open-source inference server and production cluster that allows developers to run all the models their AI agents need—from embeddings and rerankers to large language models—entirely within their own infrastructure. It solves the problem of vendor lock-in, data privacy concerns, and high costs associated with proprietary model APIs by providing a performant, self-hosted alternative. It's built for teams building production AI agents who require control, data sovereignty, and the ability to compose the best open models.

Define AI agents in JavaScript and deploy them to production in one click. Dank handles containerization, secrets, logs, scaling, and hosted vector memory so you can focus on building agents, not infrastructure.