Shaide is an open-source platform for distributed, multi-model LLM inference on Kubernetes infrastructure controlled by the deploying organization. It helps enterprise teams run private AI workloads across clusters while managing model serving and inference distribution.
Shaide is an Inference & model serving project. It focuses on running scalable, private, multi-model LLM inference across Kubernetes clusters. It is built as an open-source project for enterprise platform and infrastructure teams. Shaide is open source under the Open Source license. It runs on the web, the command line, and API, and it can be self-hosted.
It is developed by Axem Solutions. Key capabilities include multi-model inference, distributed serving, and kubernetes deployment.
Summary written by a language model from the project’s public pages.
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