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Enterprise Layer Intelligence
Categories/AI Hosting & Inference/OpenInfer
OpenInfer

OpenInfer

Founded 2024

Orchestrate, schedule, and run machine learning inference workloads across diverse hardware environments

You can use OpenInfer to schedule, route, and run AI inference workloads across heterogeneous hardware clusters. The system pools GPUs together to execute non-deterministic model requests without dropping queries under heavy traffic. You can run open models on your own servers, hybrid cloud environments, or edge nodes while migrating session states and key-value caches across machines in seconds. It also provides a hosted OpenAI-compatible cloud service, complete with customizable routing, token metering, and API key management for building custom inference endpoints.

What OpenInfer does

Schedule inference workloads across heterogeneous GPU nodesPool multiple accelerator cards into a unified compute clusterMigrate key-value caches across nodes during active sessionsTrack token usage and monitor latency SLAs per modelRoute user queries to available nodes with zero dropped requestsIssue white-labeled API keys to internal teams or external customersRun foundation models using an OpenAI-compatible API interfaceWorkload scheduling layer that packs heterogeneous models onto shared GPU clustersAutomated kernel generation targeting GPUs, CPUs, and specialized acceleratorsSubstrate-agnostic runtime for running workloads across cloud, on-prem, and edgeMicrosecond-level node recovery and failover routing without dropping user queriesFast KV cache migration between nodes to preserve context during routingWhite-labeled control tower for issuing API keys and tracking token consumptionHosted OpenAI-compatible API endpoint alternative for serverless inference

Frequently asked

OpenAIOpenAI

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OpenInfer, AI inference, GPU orchestration, model serving, workload scheduling, non-deterministic inference, heterogeneous compute, inference engine, cloud inference, token metering