The model is one part. The system is what acts.
Modern AI applications combine models with retrieval, memory, planners, tools, APIs, people and operational systems. Hood sits at the consequential boundary so intelligence can stay flexible without turning every discovered route into authority.
Do not just watch the architecture. Test the public control story.
Choose a scenario and an illustrative decision state. The visualization shows how a proposed action can proceed, pause for approval, or stop at the authority boundary. This is a conceptual demonstration only—not production policy logic.
A modern AI stack is more than a prompt and a model.
Hood is designed to work around the systems enterprises are already assembling instead of forcing them to replace their intelligence stack.
Models and planners
LLMs, multimodal models, planning loops and agent reasoning can propose actions while authority remains separate.
Retrieval and memory
RAG, vector search, enterprise knowledge and durable context inform the task without automatically expanding permissions.
MCP, tools and APIs
Tool ecosystems and connected applications create capability. Hood focuses on what those connections are allowed to cause.
Software and physical systems
Cloud, payments, enterprise systems, robotics, scientific workflows and other consequential targets can sit beyond the authority boundary.
From proposed action to governed effect.
HIOP adds a control path around consequential actions. The public architecture below names the functional stages without exposing internal policy logic, proprietary rules or implementation detail.
What this page intentionally does not expose.
Hood publishes the functional control story—identity, verification, authority, execution and evidence. It does not publish private policy logic, enforcement thresholds, credential design, internal routing, proprietary schemas, security controls or unpublished invention detail.