Overview

SIE (Superlinked Inference Engine) is your self-hosted solution for running all the open-source models your AI agents need, consolidated into a single, powerful inference cluster deployed within your own cloud environment. Say goodbye to the complexity of managing separate model servers for each task; SIE streamlines this by providing a unified API that can serve 100+ models on demand, covering everything from advanced search and retrieval to content safety and the agent loop itself.

Key Features

• Unified Inference Endpoint: Experience an OpenAI-compatible API (/v1/embeddings, /v1/chat/completions, /v1/completions, /v1/responses) for seamless drop-in migration and easy integration.
• Extensive Model Catalog: Access a pre-configured and benchmarked catalog of over 100 models, including popular choices like Stella, SPLADE, Qwen3, GLiNER, SigLIP, and more, with embedding and retrieval models rigorously tested on MTEB.
• On-Demand Model Loading: Efficiently manage resources with on-demand model loading and LRU eviction, ensuring optimal performance and cost-effectiveness.
• Production-Ready Deployment: Ships with Kubernetes and Helm deployment configurations, featuring a load-balancing gateway, KEDA autoscaling (including scale-to-zero), and Grafana dashboards for robust production environments.
• Broad Framework Support: Integrates effortlessly with leading AI frameworks and vector databases such as LangChain, LlamaIndex, Haystack, DSPy, CrewAI, Chroma, Qdrant, Weaviate, and LanceDB.
• Task Specialization: Supports critical agent tasks including search and retrieval, document-to-markdown conversion, structured data extraction/generation, content safety, and running the agent loop.

Typical Use Cases

• Empowering AI Agents: Provide a consistent and reliable inference backend for any AI agent, ensuring all its model calls are handled efficiently from a single cluster.
• Streamlining Model Management: Eliminate the overhead of managing individual model servers by consolidating all your inference needs into one unified system.
• High-Performance Search & Retrieval: Leverage advanced embedding, matching, and reranking models for sophisticated context retrieval in your applications.
• Intelligent Document Processing: Convert various document formats (PDFs, scans, Office files) into clean markdown for easier processing and analysis.
• Robust Content Moderation: Implement a safety layer with models like granite-guardian-2b to filter and assess content probability.
• Structured Data Extraction: Effortlessly extract or generate schema-valid JSON data using powerful entity and text generation models.
• Scalable Production Deployments: Deploy a resilient and scalable inference infrastructure in your cloud environment using provided Kubernetes and Helm configurations.