Build internal web apps, dashboards, workflows and AI agents with a visual low-code builder that connects to databases, APIs, SaaS and object storage. Includes AI app generation, AI query builder and AI debugging plus self-hosting and enterprise features like RBAC and audit logs.
Provides a unified platform for AI development and deployment, including the MAX serving framework and the Mojo systems programming language for writing kernels. Offers an OpenAI-compatible inference endpoint, Mojo-written CPU/GPU kernels, and tools to run hundreds of open models across diverse hardware without vendor lock-in.
Unifies enterprise knowledge into a permission-aware context layer that delivers citation-backed, explainable search and no-code or SDK-driven agentic workflow automation. Supports 50+ connectors, knowledge-graph retrieval, an MCP server, and bring-your-own-model self-hosting.
Provides isolated execution environments for AI applications, where agents can run code, manage files, and operate browsers or desktops. Deploy locally with Docker or scale on Kubernetes, with configurable network and credential controls.
Runs autonomous AI agents in isolated containers with declarative YAML policies that enforce filesystem, network, process, and inference controls. Provides credential providers, inference routing, hot-reloadable network/policy updates, and formal verification of policy changes for auditable agent execution.
Runs a Kubernetes-native runtime that multiplexes many stateful agent-like actors onto a small pool of sandboxed worker pods via full-state snapshots and pre-warmed workers, enabling sub-second suspend/resume and 30x+ oversubscription.
Creates and manages customer Kubernetes clusters on an AI factory’s NVIDIA GPU infrastructure, including cluster lifecycle and bare-metal node orchestration. It is in preview and currently supports NVIDIA Infra Controller (NICo) as its infrastructure provider.