
The fastest AI inference and reasoning on GPUs with unified control for production AI.
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Clarifai's Compute Orchestration is fully OpenAI-compatible, meaning you can switch from OpenAI to Clarifai by changing a couple of settings, without needing new SDKs or code rewrites. This allows you to immediately leverage Clarifai's faster performance, lower spend due to optimized GPU utilization, and seamless scaling for your existing OpenAI-based applications.
AI Runners securely connect your local AI models, MCP servers, and agents to the Clarifai cloud via a robust API. This enables you to instantly and securely bridge your on-premises or local AI infrastructure with Clarifai's cloud capabilities, powering any application with your local models.
Yes, Clarifai offers flexible deployment options, including the ability to deploy on bare-metal with air-gapped options. For security-conscious customers, the control plane itself can be deployed into the same cluster used for compute, enabling fully self-hosted deployments even in air-gapped environments.
Clarifai optimizes AI compute and reduces costs through features like GPU fractioning, batching, and autoscaling. It automatically manages resources and supports the use of spot instances. The platform's optimized runtime maximizes GPU utilization for each model replica, leading to over 90% less compute required compared to traditional methods.
The AI Lake is a central repository for all your AI assets, including inputs, vector embeddings, datasets, annotations, models, workflows, and modules. It provides a unified place for teams to organize, share, and reuse these assets, accelerating AI adoption and reusability across the enterprise while enabling access control and tracking lineage and versioning.
Clarifai provides a full lifecycle platform including Spacetime for vector search and data management, Scribe for automated data labeling, Enlight for model training and evaluation, Armada for auto-scaling model inference, Mesh for drag-and-drop workflow creation, Extend for building custom Streamlit UIs, and Collectors for continuous learning data collection.
Source: clarifai.com