One Server to Serve Them All: How the Superlinked Inference Engine replaces a zoo of AI model servers with a single, open-source system
Building an AI product often means running a crowd of small models: one for embeddings, one for reranking, one for extraction, one for OCR, and another to write answers. Each usually gets its own server, and its own headaches. This engine replaces that patchwork with one cluster serving more than 100 models, loaded only when needed. With four simple verbs (encode, score, extract and generate) and a few lines of Python, teams can go from laptop to Kubernetes without rewriting code.