Context

Context is a unified platform designed for enterprises to build, deploy, and improve AI agents in production environments. It addresses the need for robust, self-improving agents by providing a comprehensive workspace where both teams and AI agents can collaborate on documents, spreadsheets, decks, kanbans, and files within the same environment. The platform supports a range of industries, including financial services, semiconductors, consulting, telecom, public sector, industrials, business operations, insurance, BPO, and legal, indicating its focus on large-scale, enterprise use cases.

A core feature of Context is its ability to integrate with over 800 connectors, allowing seamless access to tools commonly used by enterprise teams. It offers modules and workflows that can be authored in plain English, making it accessible for a variety of roles and use cases. The platform includes a context graph that enables agents to capture and reuse knowledge, and permissions are enforced according to user grants, with full audit logs on every action. Identity is inherited from the user's identity provider (IdP), supporting enterprise-grade authorization and customer-managed keys for security.

Context supports deployment in multiple environments: it can be hosted, run within a customer’s own VPC, on-premises, or in air-gapped configurations. The platform is compatible with a range of AI models and agent frameworks, including Claude, GPT, Gemini, Kimi, Llama, and custom models, as well as user-provided agent frameworks. Custom models can be trained on a team’s accepted outputs, turning them into training data for models owned and served by the customer. The platform includes evaluation tools such as rubrics and golden sets to validate every runbook, model, and context change, ensuring quality and catching regressions automatically. Step-level model routing is used to optimize cost and quality by assigning tasks to the most appropriate model for each step.

Context emphasizes continuous improvement, auditability, and production readiness for enterprise AI agents. It is positioned as a solution for organizations seeking to operationalize and scale AI agent workflows securely and efficiently.