# Glossary

Key terms used throughout the ADI documentation.

## Product terms

**ADI (Agentic Data Intelligence)**  
The control plane for AI data analytics. A thin layer between agents and your data that generates a machine-readable model of what your data means and an enforceable contract constraining how AI agents use it.

**Starter Edition (SE)**  
The ADI edition for individual developers, data engineers, and analysts. Delivered as a plugin bundling the Skills and MCP server, for coding agents and IDEs.

**Enterprise Edition (EE)**  
The ADI edition for teams and organisations. Delivered as a native app inside the customer's own cloud data warehouse.

**Control plane**  
The role ADI plays: it does not query the data itself, it governs how agents and copilots query, holding them to the contract.

**Contract**  
A structured definition of what data can be queried, how it should be measured, and what governance rules apply. The single source of truth for all agents and queries. Also called a "consumption contract".

**Contract bundle**  
The set of YAML documents that make up a contract: the contract definition, entities, metrics, and vocabulary (required), plus policies and rules (optional).

**Trust tier**  
The level at which a Starter Edition instance runs, reflecting how much of the workflow the platform runs on your behalf. The Beta runs at t1 (generation and validation only). t0 (self-hosted) and t2 (fully hosted with credentials) are the execution tiers, planned for future releases.

## Architecture terms

**Data Asset Layer (DAL)**  
The first layer. What data physically exists and how it is structured: schemas, tables, columns, keys, and relationships.

**Business Model Layer (BML)**  
The second layer. What the business cares about: entities, events, and the relationships between them. Maps physical data to business concepts.

**Analytical Model Layer (AML)**  
The third layer. How the business can be measured: dimensions, metrics, and the rules for calculation and aggregation. Can be output to MetricFlow as an output sink.

**Consumption Contract Layer (CCL)**  
The fourth layer. Defines how users and agents are allowed to ask questions: supported intents, default behaviours, and guardrails. The system-level enforcement of correctness.

**Four-layer architecture**  
ADI's approach to building understanding of data, each layer adding meaning on top of the one below: Data Asset Layer, Business Model Layer, Analytical Model Layer, Consumption Contract Layer.

**Semantic model**  
The complete understanding ADI builds of your data: what it is, what it means, how it can be measured, and how it can be queried. Encompasses all four layers.

## Technical terms

**MCP (Model Context Protocol)**  
An open standard for connecting AI agents to external tools and data sources. ADI exposes its tools as an MCP server.

**SKILL.md**  
A file following the Agent Skills Specification that contains instructions for an AI agent: which tools to call, in what order, how to author and validate a contract, and how to handle responses.

**Plugin**  
A bundle of the Skills, the MCP server, and potentially other elements, so your agent can get started without installing each individually. The plugin is the recommended way to install Starter Edition, with dedicated plugins for Claude Code, Cursor, and Codex; see Getting Started for the install commands.

**FastMCP**  
The MCP server framework ADI uses to expose its tools.

**adi.get_capabilities**  
The tool that reports the active trust tier, the enabled features (including whether execution is available), and the tools you can call.

**adi.get_authoring_spec**  
The tool that returns ADI's canonical contract schema and authoring guidance, used when authoring a contract for your own data.

**adi.validate**  
The tool that machine-validates a contract bundle against the canonical schema, returning path-pointed errors for anything that needs fixing. At t1 it runs structural and semantic checks; warehouse-tier validation needs the execution tiers.

**adi.generate_query**  
The tool that compiles a structured request into contract-governed SQL, returning the SQL, its provenance, and a plain-language explanation, or a refusal.

**Recommended workflow**  
Discover capabilities (`adi.get_capabilities`), author and validate a contract (`adi.get_authoring_spec`, `adi.validate`) or load a provided one, then generate governed SQL (`adi.generate_query`). At t1 you run the generated SQL in your own environment; at the execution tiers the server can run it directly.

## Governance terms

**Refusal**  
ADI's response when a request asks for something outside the contract. Carries a code, a message, the relevant contract path, and recovery information (such as the allowed metrics or group-bys). A refusal is expected control flow, not an error. Codes are lower_snake_case and include `request_malformed`, `metric_not_found`, `dimension_not_allowed`, `dimension_disallowed`, `policy_denied`, `join_path_absent`, `high_cardinality_refused`, and `contract_not_cached`; see the Features page for the full set.

**Safe alternatives**  
Recovery information returned with a refusal: the metrics, group-bys, or related requests the contract can answer.

**Policy classification**  
The labelling of sensitive columns in the contract's policy document (for example `pii`, `sensitive`, `confidential`) with an action such as deny, mask, or redact. Enforced before data reaches any agent.

**Signature**  
A token in the form `adi-sql-v1:<sha256>` proving a generated query was compiled from the contract. It is produced at the execution tiers (t0 and t2), where it gates execution so only contract-compiled SQL runs. The t1 Beta is generation-only and does not produce a signature.

**contract_hash**  
A hash identifying a validated contract. Can be reused on later `adi.generate_query` and `adi.validate` calls instead of resending the full contract documents; the Beta caches contracts for 24 hours.

**Provenance**  
The traceable chain from request to result: the metric used, the entities and joins involved, the group-bys and filters applied, the policies honoured, and a plain-language explanation. Returned on every generated query.

## Data terms

**Metric**  
A defined measurement in the contract (for example order count, total revenue). Metrics have a fixed calculation type (sum, count, count_distinct, or ratio) and are consistent across all agents and sessions.

**Dimension**  
A category for grouping or filtering metrics (for example country, product). The contract defines which dimensions are allowed for each metric.

**Entity**  
A business object in the data model (for example organisations, users, orders). Entities have relationships defined in the Business Model Layer.

**Vocabulary**  
Synonym lists for metrics and dimensions, included in the contract to help agents match natural-language terms to the correct contract fields.

## Workflow terms

**Human-in-the-loop**  
ADI's operating model where humans stay in control. Agents handle routine work; humans approve changes to the semantics and the contract and define what matters to the business. Enterprise Edition adds a Slack-based governance process.

**Agentic loop**  
ADI's continuous cycle: sense changes in data and schema, update understanding, answer questions within boundaries, enforce the contract, and learn from reviewed feedback.