What AI tool lets me ask questions about my company's data in plain English?

Summary

• Genie Agents is a conversational AI interface built into Databricks that translates natural language questions into SQL queries automatically.
• Users type questions in plain English and get data results instantly, without needing SQL expertise or waiting for analysts to write queries.
• The system learns from your data schema, dashboards, and semantic layer to provide accurate answers that respect security policies and business definitions.

What AI tool lets me ask questions about my company's data in plain English?
Genie Agents is a natural-language query interface that brings conversational AI to your data warehouse. Type or speak a question about your company's data in plain English, and Genie translates it to SQL, executes it, and returns results. No SQL knowledge required. Business users can explore data independently instead of submitting requests to analysts, who can focus on higher-value work like building dashboards and designing data models.

How natural language query works

When you ask Genie a question, it performs these steps in seconds:

1. Understands your schema: Genie reads the list of available tables, columns, and their definitions from your Databricks lakehouse.
2. Infers intent: It determines what data you're asking for and which tables to query.
3. Generates SQL: It writes a SQL query that answers your question.
4. Executes safely: The query runs on your lakehouse, respecting all row-level and column-level security policies.
5. Returns results: Genie displays the results with visualizations (tables, charts, or raw data depending on the answer).
6. Handles follow-ups: You can ask clarifying questions, drill down, or refine. Genie keeps context across the conversation.

What makes natural language data access effective

Factor	Why it matters
Speed	Get answers in seconds instead of waiting hours for analysts to write and review queries
Accessibility	Business users explore data without SQL training, reducing bottlenecks
Accuracy	Genie uses your semantic layer and business definitions, not guesses
Security	All queries respect data governance automatically (Unity Catalog)
Iteration	Follow-up questions keep context, enabling exploratory analysis
Integration	Works with dashboards, BI tools, and existing workflows

How Databricks builds natural language interfaces

Genie is built into the Databricks AI/BI interface and connects directly to your lakehouse. It's powered by large language models fine-tuned for data queries, but grounded in your actual schema and semantic context.
Schema understanding: Genie ingests your table names, column names, data types, and descriptions from the Unity Catalog. This grounds it in reality: it knows which columns contain customer names, which contain revenue, and which are foreign keys.
Semantic layer integration: If you build AI/BI Dashboards with defined metrics and dimensions (your "semantic layer"), Genie uses those definitions. For example, if your dashboard defines "Q3 revenue" as a sum of specific transactions, Genie applies that same definition rather than guessing.
Conversational continuity: Genie maintains context across multiple questions in a conversation. You can ask "What was revenue in Q3?" then follow up with "Compare that to Q2" without re-specifying what you mean by revenue.
Real-time results: Queries run against your live lakehouse, so you always get current data.

Use cases

Sales: "How many deals closed in the financial services vertical last month, and who were the top three account executives?" Genie queries your CRM, filters by vertical and close date, and ranks by owner.
Finance: "What was our gross margin by region for the last quarter?" Genie combines revenue and cost data, groups by region, and returns a comparison table.
Product: "Which features have the highest adoption among customers in Asia?" Genie joins product events to customer metadata, filters by region, and ranks features by usage.
HR: "How many employees in engineering have tenure over three years, and what's their average salary band?" Genie queries the employee directory, applies the tenure filter, and summarizes by salary band.

FAQs

Can Genie Agents replace data analysts?

No. It reduces their day-to-day query-writing work. Analysts shift to designing schemas, building dashboards, creating semantic layers, and doing high-value analytics like anomaly detection or forecasting. Genie handles the routine questions.

What if Genie misunderstands my question?

For ambiguous questions, Genie can ask for clarification. You can rephrase, provide examples, or drill down to clarify your intent. The system learns from corrections and improves over time.

Does Genie respect my data security?

Yes. All Genie queries respect row-level and column-level access controls from Unity Catalog. If you can't see a table or column, Genie won't include it in queries on your behalf.

What languages does Genie support?

Genie is optimized for English queries, though it can handle questions written in other languages. The output is typically in the language of your data (SQL, column names, table names) and any business definitions you've stored.