These agents act as a bridge between your business teams and your databases. They translate natural language questions into safe, optimized SQL queries and return answers instantly.
Converts questions like "How many active users signed up last week?" into precise SQL queries automatically.
Not sure what a query does? The agent explains the logic in plain English, ensuring transparency and trust in the data.
Writes efficient code that respects database load, avoiding expensive scans and unoptimized joins.
Automatically learns your database structure, table relationships, and column names to generate accurate queries.
Enforces read-only access (SELECT only) and PII masking, preventing accidental data modification or leaks.
Understands your business jargon (e.g., "ARR" vs "MRR") and maps it to the correct underlying tables.
Can query across different databases simultaneously to give you a holistic view of your data universe.
Saves successful queries to a team library, allowing anyone to re-run complex reports with a click.
If a query fails, the agent self-corrects the syntax error and retries until it gets the valid result.
Empower every team member to be a data analyst without learning a single line of code.
Supports complex questions with filters, timeframes, and aggregations ("Show daily active users by country for last month").
SOC 2 compliant, read-only permissions, and on-premise deployment options for maximum data safety.
Returns data as clean tables, JSON, or instantly visualizes the results as charts.
Download results immediately to CSV or Excel for further modeling or sharing.
Share queries and results via link, Slack, or email directly from the agent interface.
Audit trail of every question asked and every query generated for compliance and learning.
Seamlessly connects to the most popular SQL and NoSQL databases and data warehouses.
PostgreSQL, MySQL, Microsoft SQL Server, MariaDB, Oracle Database
Snowflake, Google BigQuery, Amazon Redshift, Databricks, Azure Synapse
MongoDB, Amazon DynamoDB, Redis, Cassandra (via SQL connectors)
CSV, Parquet, JSON, Excel (XLXS), Google Sheets
Looker, Tableau, Power BI, Metabase (can import/export models)
REST API, GraphQL, Python SDK, Node.js SDK
How high-growth companies are democratizing data access with AI SQL Agents.
Time Saved
Problem: The 3-person data team was overwhelmed with basic requests from Sales ("Who logged in today?", "What's the usage for Acme Corp?"). Solution: Deployed an AI SQL Agent that allows Sales Reps to ask these questions directly continuously and securely.
"Our data engineers can finally focus on infrastructure instead of pulling CSVs all day. The Sales team loves the instant answers."
— James Torrez, CTO at CloudScale
Ops Efficiency
Problem: Warehouse managers needed to know stock levels instantly but couldn't write SQL to query the main database. Solution: An AI interface on their tablets lets them voice-query: "Show me low stock items in Zone B."
"We've eliminated the 'middleman lag'. Managers make decisions on the floor based on live data, not yesterday's reports."
— Sarah Liu, VP of Operations
Risk & Compliance
Problem: Giving analysts direct DB access was a security risk. Every query needed to be vetted. Solution: The AI SQL Agent acts as a secure middleware, allowing query freedom but strictly enforcing read-only policies and PII redaction.
"We now have a perfect audit trail of every question asked. It's actually more secure than giving direct SQL access."
— Michael Ross, CISO
Common questions about connecting AI agents to your databases.
Empower your entire organization to make data-driven decisions without waiting on the data team.