# Use Cases

ADI serves different users depending on the edition. Starter Edition is for individuals working with coding agents and IDEs. Enterprise Edition is for teams adding a semantic and control layer to copilots and agents on cloud data platforms.

## Starter Edition use cases

### Developers adding semantic and control functionality to agentic workflows

Individual developers building AI agents can give those agents governed, meaning-aware data access without writing custom data logic. The ADI plugin, bundling the Skill and MCP server, provides the semantic layer, the governance rules, and contract-checked SQL. The developer's agent works in business terms and receives verified, provenance-tracked results.

### Data engineers extending coding agents

Data engineers working in Claude Code, Cursor, or other coding agents can query governed data within their existing workflow. The contract keeps metric definitions consistent across sessions and agents. Schema knowledge is not required: the contract defines the valid surface area.

### Analysts using AI agents for governed queries

Analysts who work with AI agents can ask questions governed by the contract. ADI refuses questions that fall outside the contract and points to safe alternatives. The analyst gets answers backed by a declared definition, with provenance showing how those answers were derived.

## Enterprise Edition use cases

### Teams governing the copilots and agents they already run

Teams adopting copilots and agents on the warehouse often hesitate, because they cannot trust what the agent does with the data. ADI adds the semantic and control layer above those tools: it constrains how they query and enforces what the metrics mean, so business users can self-serve through an agent without the team losing control.

### Consistent, governed self-serve analytics

Ask questions in business language and get validated answers with provenance. Because the contract defines the metrics once, every user, session, and agent works from the same definitions, so the same question returns the same answer within that shared contract. Governance is applied by the contract rather than left to policy on paper.

### Managing change and drift

Semantics go out of date fast. When source schemas or business rules change, ADI detects the change, updates its understanding, and keeps enforcement consistent across all downstream consumers. Changes to the semantics and contract are versioned and reviewed, so they can be rolled back.

### Cross-domain data work

ADI works across data domains: financial data, operational data, marketplace data, even blockchain data, whether your own or from marketplaces. The same four-layer architecture applies regardless of the business domain. The contract defines what the data means and how it can be queried, and that approach is domain-agnostic.

## Platform integrations

### Starter Edition

**Dedicated plugins:** Claude Code, Cursor, Codex.

**Compatible plugins and skills:** OpenClaw, Manus, and any other coding agents that support either the Open Plugins Specification or the Agent Skills Specification.

**Delivery:** the ADI plugin, which bundles the Skills (Agent Skills Specification / SKILL.md) and an MCP server (Model Context Protocol, built on FastMCP); the Skills and MCP server can also be installed individually. Domain Packages for different data types are planned for future releases.

### Enterprise Edition

**Data platforms (available now):** Snowflake, Databricks.

**Data platforms (coming soon):** Google BigQuery, Amazon Redshift.

**Interoperability:** The contract's analytical model can be output to MetricFlow, with two-way Open Semantic Interchange (OSI) compatibility planned for a future version.