Superlinked
Superlinked builds an open-source inference engine that serves task-specific open models for search, reranking, document processing, classification, vision, speech and generation, cutting the cost of AI agent workloads.
Superlinked is an AI inference infrastructure company founded in 2021 and headquartered in San Francisco. It reduces the cost, latency and infrastructure complexity of AI agents that repeatedly call general-purpose models by serving task-specific open models instead. The central product is the Superlinked Inference Engine (SIE), an open-source inference engine that serves models for ten capabilities: search, reranking, document processing, extraction, classification, content safety, image understanding, audio transcription, chat and generation.
The broader open-source stack includes a Model Gateway that routes and selects models against measured quality targets, Python and TypeScript SDKs, an MCP (Model Context Protocol) server for agent and tool interoperability, and Helm charts and Terraform deployments for running SIE on Kubernetes and major cloud providers. Autoscaling and monitoring for inference workloads are part of the same stack. For teams that prefer not to self-host, the SIE Serverless API provides access to the same task-specific models and interfaces as the self-hosted engine.
Deployment options range from a local laptop to private clusters, a customer's own cloud or Kubernetes environment, or the hosted Serverless API. The system shares GPUs across multiple model types, and the company emphasises keeping customer data and AI workloads within customers' own infrastructure. Engineering work spans model serving and gateways, GPU utilisation, search and reranking, document processing, computer vision, speech-to-text and conversational AI, as well as SDK and deployment tooling for ML and platform engineers and software teams.