# Glossary **Agent** — An AI model that carries out a task with tools: reading metadata, checking quality, measuring a proposal. An agent runs in an isolated container and never gets a model vendor key or a database password. **AI gateway** — The point every request to an AI model passes through, with exactly one policy decision per request. See [The AI gateway](/concepten/ai-poort). **Cohort threshold** — Counts below ten become "<10", so no individual can be inferred from a count. **Connector** — A link to a system that is not a database, such as Power BI, Azure Data Factory, SharePoint or Databricks. See [Sources and connectors](/bronnen/overzicht). **Customer** — The shielded space where sources, rules, knowledge and permissions come together. Can also be a department. **Customer profile** — A layer between platform and customer, for skills and knowledge that apply to a kind of customer. **Data access** — The mode per source that determines what an AI model sees: metrics only, encrypted values or open. See [Data access](/concepten/datatoegang). **Dataset** — A reusable definition of data for dashboards: one query on one source, or a derived dataset that combines other datasets. See [Datasets](/dashboards/datasets). **Encrypted values** — The data access mode in which every cell is a stable token. The model can count and join without seeing the value. **Environment** — Production, acceptance, test or development. Every source belongs to an environment. **Finding** — What is created when a monitor sees a deviation. At most one open finding per monitor. **First responder** — The part of the platform that answers simple questions in a conversation directly and hands heavier work to an agent itself. **Ground rules** — The agreements that apply to all tasks for a customer: models, budget, data access, guidelines. Every change is a new version. See [Ground rules](/beheer/spelregels). **Knowledge document** — Background information that goes along with an agent, such as a data dictionary. See [Skills and knowledge](/concepten/skills-en-kennis). **Landscape** — The map of an environment: systems, databases, pipelines, datasets, reports and their connections. See [Environments](/concepten/omgevingen). **MCP** — Model Context Protocol, the open standard that lets an AI tool use tools from a server. With MCP you connect your own AI tool to the platform. See [Connecting via MCP](/eigen-ai/mcp-koppelen). **Metrics only** — The strictest data access mode: structure, counts and statistics, no rows. The default. **Monitor** — A scheduled check by an agent that gives a verdict. See [Monitors](/concepten/monitors). **Open** — The data access mode in which literal values go to the model. Only for sources the customer designates. **Proposal** — A change an agent proposes that is only carried out after a human approves it, for example a script on a source or a new skill. **Pseudonym** — The replacement name under which a table, column or value goes to the model, such as `t_0056`. See [Pseudonymisation](/concepten/pseudonimisering). **Sandbox** — A disposable copy of the database in which an agent runs and measures its proposal. See [The verification sandbox](/concepten/sandbox). **Skill** — A work instruction that goes along with an agent. See [Skills and knowledge](/concepten/skills-en-kennis). **Solo** — The way of working in which all work happens in your own AI tool and the platform only supplies tools, rules and storage. See [Solo](/eigen-ai/solo). **Source** — A customer database or system the platform works on, for example an Azure SQL database, a PostgreSQL server or a Power BI workspace. **Task** — A piece of work on the platform, with a goal, a work mode, allowed sources and a history. A conversation is a task too. **Work mode** — What an agent may do in a task: look only, measure on the source, or prove on a disposable copy. See [Work modes](/concepten/werkmodi).