Cortega: Enterprise AI Governance in the Request Path

Research Context and Background

Cortega is an enterprise AI governance platform designed to provide a unified solution for observing AI usage, applying policies, protecting sensitive data, governing Model Context Protocol tools, routing models, and controlling costs. Unlike traditional security tools that operate as add-ons, Cortega is built to run directly in the request path on infrastructure you control, working seamlessly across clouds, providers, and local models.

Benefits

Cortega offers several key advantages for organizations managing AI systems. It operates by intercepting and managing AI traffic before it reaches external providers. Its workflow follows a strict sequence for every request. First, it verifies authentication to ensure only authorized entities access AI resources. Next, it inspects prompts and responses to detect sensitive data like personally identifiable information and potential attacks. Then, it enforces defined policies before the request proceeds. This includes blocking, redacting, routing, or requiring human approval. Finally, it records evidence mapped directly to compliance controls to ensure auditability.

Key features include infrastructure control, allowing deployment on your own infrastructure to keep sensitive prompts aligned with your operating requirements. It supports on-premise, cloud, and hybrid environments. The platform enforces policies before AI requests and tool calls proceed, preventing data leakage or unauthorized access at the source. It detects sensitive data without requiring a separate scanner and provides specific governance for MCP tools to mitigate risks from prompt injection and unexpected agent behavior. The platform also offers centralized management for Single Sign-On, Role-Based Access Control, audit evidence, routing strategies, budgets, and model selection. It integrates with the entire AI stack, including major providers like OpenAI, Anthropic, and Meta AI, as well as frameworks like LangChain and tools like MCP.

Use Cases

Cortega is designed for teams looking to move AI from promising development demos to controlled production use. While regulated data often drives the initial need, the platform's controls also address shadow AI by mapping and controlling unauthorized AI usage. It helps with budget management by tracking and controlling AI spend across the enterprise. The platform supports quality assurance by monitoring the quality of AI outputs and interactions. It also provides governance for Model Context Protocol tools to manage associated risks. By starting with the operating problem, Cortega provides the necessary visibility and enforcement to ensure AI adoption is secure, compliant, and efficient.

Pricing

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Additional Information

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