Machine Learning Infrastructure

Execute AI-generated code safely with 90ms sandbox creation, isolated environments, and enterprise-grade security. Perfect for AI agents and development workflows.

Universal memory layer for LLM applications that learns from user interactions, reduces token costs by 80%, and delivers personalized AI experiences.

Open-source vector database designed for AI applications. Store, search, and retrieve embeddings with semantic similarity matching and metadata filtering.

Add persistent memory to LLM apps with millisecond recall times. Store, retrieve, and personalize user data across sessions with enterprise-grade security.

Letta is an open-source platform for creating AI agents with built-in memory, reasoning, and support for thousands of tools.

Open-source vector database designed for building powerful, production-ready AI applications with hybrid search capabilities and flexible deployment options.

Deep Lake is an open-source database for storing, querying and managing complex AI data like images, audio, and embeddings.

Open-source platform for logging, monitoring, and debugging LLM applications. Route, debug, and analyze AI apps with comprehensive observability tools.

Laminar is an open-source platform that helps collect, understand, and utilize data for building high-quality LLM applications.

Open-source observability platform for GenAI and LLM applications. Real-time monitoring, distributed tracing, prompt management, and AI model evaluation built on OpenTelemetry.

Run AI workloads with sub-second cold starts, elastic GPU scaling, and secure sandboxed environments. Scale to zero when idle, burst to thousands instantly.

Open source platform for ML engineers to track metrics, parameters, and gradients in real-time. Features Git integration, alerts, and seamless workflow integration.