AI can expand how users explore data inside your product, help your team build and refine dashboards faster, connect governed analytics to the AI tools where they already work, and help your team build Luzmo integrations more efficiently.
In this article, you will learn how to:
The most important distinction is who the AI is helping.
| Goal | Recommended approach | Who benefits? |
|---|---|---|
| Let users ask questions about their data in natural language | Luzmo IQ | Users inside your application |
| Build charts and dashboards faster using AI assistance | AI-powered chart & dashboard creation | Analysts and dashboard builders |
| Give an existing agent access to governed analytics | Luzmo MCP server | Users working in your agent or an AI tool |
| Build dashboards, integrations, queries, or embed flows faster | Luzmo Agent Skills and the Luzmo API | Your developers and analytics team |
These approaches are complementary. For example, you can offer Luzmo IQ inside your application, let your analysts build the surrounding dashboards faster with AI assistance, expose the same governed analytics to another agent through MCP, and use Agent Skills to help your developers build the surrounding experience.
Here are a few concrete examples:
| Scenario | What the user asks for | Luzmo approach |
|---|---|---|
| A product manager is investigating feature adoption | "Compare weekly adoption for SMB and enterprise customers over the last 90 days." | Luzmo IQ |
| An analyst is putting together a new monitoring dashboard | "Build me a dashboard tracking weekly active users, retention, and churn by segment." | AI-powered dashboard creation |
| A customer success manager is preparing for a renewal | "Show me which renewing accounts had a usage decline of more than 20% this month." | Luzmo IQ, optionally exposed through MCP |
| A sales assistant already uses CRM and email tools | "Find my at-risk opportunities, visualize recent product usage, and prepare a follow-up." | A broader agent using the Luzmo MCP server for the analytics step |
| A developer is building a multi-tenant analytics page | "Create a React embed that loads the correct dashboard and data for the signed-in customer." | Agent Skills and the Luzmo SDK |
Luzmo IQ lets users explore data by asking questions in natural language instead of navigating a fixed sequence of dashboards and filters. It's useful for self-service exploration, follow-up questions after viewing a dashboard, and guided analysis for non-technical users.
How did monthly recurring revenue change this quarter, and which regions contributed most to the decline?
Go deeper in this course: Luzmo IQ and Luzmo IQ implementation tips and tricks. For embedding IQ in an agentic workflow, see Adding Luzmo IQ to an agentic workflow.
Beyond answering questions, Luzmo's AI can help the person building a dashboard move faster — generating a first chart from a plain-language description, and assembling a full dashboard from a stated goal rather than one chart at a time.
Build me a dashboard tracking weekly active users, retention, and churn by segment, for the last two quarters.
This is a different capability from Luzmo IQ: IQ answers a question for an end user exploring data, while AI-assisted authoring helps a builder create the reusable dashboard other people will later explore.
Go deeper in this course: AI powered chart generation and editing and AI-assisted dashboard building.
The Luzmo MCP server exposes analytics capabilities to an agent, so it can discover data, ask analytical questions, or generate visualizations as part of a broader conversation or workflow — with Luzmo acting as the governed analytics layer rather than the entire agent.
Which of my accounts renewing in the next 60 days have declining product adoption? Show their eight-week usage trend and prepare a short briefing for each one.
MCP is built for embedded, customer-facing use cases: it carries the authenticated user's identity, data access, and product context into the analytics request, so end users never need to manage Luzmo API keys directly.
Go deeper in this course: see Luzmo MCP server: governed analytics for AI agents and Keeping MCP access safe and governed. For setup and reference, see Luzmo MCP introduction on developer.luzmo.com.
AI coding assistants such as Claude Code, Cursor, Codex, Windsurf, Google Antigravity, and GitHub Copilot can help you build and maintain Luzmo integrations — embedding dashboards, writing server-side authorization, querying data, or troubleshooting embed issues. Luzmo Agent Skills give supported assistants Luzmo-specific instructions and implementation patterns.
Create a React component that embeds a Luzmo dashboard. Assume the authorization key and token are fetched from a server-side endpoint. Add loading and error states, and do not place API credentials in client-side code.
Go deeper in this course: see Luzmo Agent Skills: AI assistants that know Luzmo. For installation and reference, see the Luzmo Agent Skills guide on developer.luzmo.com.
Use the following rule of thumb:
You may use several of these together — they address different layers of the same solution. AI is most useful in Luzmo when it reduces the distance between a question and a trustworthy answer, or between an idea and a working dashboard.