Lakehousecat AI Agent
The Lakehousecat AI Agent is a conversational assistant built into every session. It understands your data, executes analytical tasks in natural language, and — depending on your role — can manage datasources, models, users, and platform resources.
How It Works
The Agent operates within a session. You type a request in plain language; the Agent interprets it, selects the appropriate action, and returns a result — a chart, a table, a confirmation, or a follow-up question.
The Agent is role-aware: the set of actions it can perform expands with the permissions assigned to your account. A standard user can generate charts and manage their own sessions. A builder can create datasources and models. An admin has full platform management capabilities.
Capabilities by Role
| Capability Area | User | Builder | Admin |
|---|---|---|---|
| Generate charts and analyze data | ✅ | ✅ | ✅ |
| Manage own sessions and prompts | ✅ | ✅ | ✅ |
| Manage charts and dashboards | — | ✅ | ✅ |
| Create and configure datasources | — | ✅ | ✅ |
| Create and manage AI models | — | ✅ | ✅ |
| Update semantic descriptions | — | ✅ | ✅ |
| Schedule and manage jobs | — | ✅ | ✅ |
| Install sample packages | — | — | ✅ |
| Manage users and groups | — | — | ✅ |
| Monitor platform instance & license | — | — | ✅ |
| Back up and restore the instance | — | — | ✅ |
| Review the audit log (who changed what) | — | — | ✅ |
The Agent Remembers You
The Agent maintains a personal memory for each user. When you share a preference — such as a preferred language, a chart style, or a response format — the Agent stores it and applies it automatically in all future interactions.
You do not need to repeat preferences in every session. Once set, they persist.
Examples:
- "Always give me feedback in English." → The Agent responds in English from that point on.
- "I prefer horizontal bar charts over vertical ones." → Applied automatically when the Agent chooses a chart type.
- "Keep your answers short and skip the explanations." → The Agent adjusts its response style accordingly.
The Agent also learns implicitly from your interactions over time — the chart types you prefer, the level of detail you engage with, and the patterns in your requests. You are always in control: you can instruct the Agent to forget a specific preference, or to clear everything it has learned about you.
How to Interact
The Agent responds to natural language. Phrase your request as you would ask a knowledgeable colleague:
- "Show me a bar chart of revenue by region for the last 6 months."
- "Create a new datasource for our production PostgreSQL database."
- "Add user anna@example.com to the Analytics group."
- "What is the current license state of this instance?"
The Agent infers intent from context. You do not need to know command syntax or API endpoints.
Role Guides
For a detailed view of what each role can do with the Agent:
- User Capabilities — Chart generation, sessions, prompts
- Builder Capabilities — Data, models, semantic layer, jobs
- Admin Capabilities — Users, groups, sample packages, backup and restore, audit log, instance monitoring