Clarifai’s AI Lake™ product provides a unified, central repository for consolidating and managing all AI assets, such as models, annotations, datasets, workflows, and user interfaces. This enables teams to collaborate more effectively, share resources, and reuse AI components across various applications, significantly streamlining the process of integrating AI into their products and services. The platform is designed to optimize AI workflows by centralizing assets for improved organization, reusability, and enhanced collaboration in application development. AI Lake™ supports the storage and analysis of massive amounts of diverse data objects, including raw data, annotations, datasets, models, model evaluations, modules, predictions, vectors, and workflows, which can be organized into applications or projects. It ensures optimal GPU usage through intelligent inference orchestration that maps models to the most efficient CPUs or GPUs. Its battle-tested endpoints handle massive autoscaling with fully configurable scaling policies, allowing for effortless accuracy versus performance trade-offs in real-world applications. The platform facilitates robust data governance by enabling users to organize data into versioned datasets, automatically or manually ingesting data while tracking every change. It provides comprehensive lineage and versioning tracking for all AI assets, detailing their origin and usage over time. Granular access control allows organizations to decide which individuals, teams, and processes can access, modify, or delete any AI resource, ensuring security and compliance. Furthermore, AI Lake™ promotes reproducibility by enabling the recreation of AI application or model results using the exact input data, code, and configurations. Clarifai AI Lake™ offers enterprise-grade AI infrastructure with 99.999% uptime, significantly reducing the need for extensive software reliability engineering investments. It integrates seamlessly with existing IT infrastructure, supporting deployments on major cloud providers like AWS (including C2S), GCP, and Azure, as well as on-premise bare metal systems, including air-gapped secure client premises. By making AI assets findable and reusable, the platform accelerates AI adoption across the enterprise, avoids redundant efforts, encourages collaboration, and empowers data scientists to build accurate models faster by eliminating grunt work, all while improving AI governance through auditable provenance and change history.

Features & Benefits

• Centralized AI Asset Management
  • Consolidates and organizes all AI assets in one central place, including models, annotations, datasets, workflows, and UIs, to foster collaboration and reusability.
  • Store data, annotations, datasets, models, model evaluations, modules, predictions, vectors, and workflows.
  • Organize assets into applications or projects.
• Optimized Resource Utilization & Scalability
  • Ensures optimal GPU usage sharing and provides battle-tested auto-scaling, mapping models to the most efficient CPUs or GPUs and handling massive autoscaling with configurable policies.
• Data & Model Governance
  • Organizes data into versioned datasets, tracks lineage and versioning for all AI assets, controls access to AI resources, and ensures reproducibility for auditing and consistent results.
• Enterprise-Grade Infrastructure & Integration
  • Delivers 99.999% uptime, reduces software reliability engineering investments, and integrates seamlessly with existing IT infrastructure, supporting AWS, GCP, Azure, on-prem, and air-gapped systems.
• Accelerated AI Development & Collaboration
  • Facilitates faster AI adoption and reusability across the enterprise by making AI findable, avoiding redundant efforts, encouraging sharing, and streamlining the model building process for data scientists.