Context

Context provides a platform where teams can build, run, and improve AI agents inside their own infrastructure. It combines a workspace, runtime engine, and evaluation system to support production-grade agent workflows. The product emphasizes operating under a company’s controls, with agents that can access company data and tools.

The workspace unifies chat, files, tasks, and skills with agents as named members, enabling permission-based collaboration and traceable actions. It aims to bring agents, humans, and assets into a shared environment where tasks and decisions are recorded and accessible.

The engine runs agents and can integrate with various models and endpoints, offering per-task sandboxes and durable runs. It supports scheduling and automation to handle recurring workflows while maintaining auditability and guardrails.

The help and product pages describe deployment options, security features, connectors, and model choices, indicating a breadth of capabilities across deployment, security, and integrations. The platform is suitable for production work, with options for on-premises, air-gapped, and cloud deployments.

Use cases

• Build the Q3 portfolio review deck from updates and the valuation bridge.