inference Tools

vLLM is a high-throughput and memory-efficient inference and serving engine for Large Language Models (LLMs). It solves the problem of expensive and inefficient LLM deployment by maximizing hardware utilization with features like PagedAttention and continuous batching, drastically reducing inference costs. It's designed for developers and organizations who need to deploy a wide range of open-source LLMs easily and affordably on any hardware, offering a drop-in OpenAI-compatible API for instant integration.

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.