Summary : Quick Demo An AI agent can be empowered to query internal data sources by equipping it with tools that interact directly with n8n’s native Data Tables. In this example, a “Sales Data Agent” is connected to a series of tools, each designed to query a sales database in a specific way—by product name, date, product ID, or to perform calculations. 00:02 When asked a question in natural language, such as, “How much total revenue have we made from our bluetooth speaker?”, the agent intelligently selects the appropriate sequence of tools. It first uses the “Product Name Query” tool to retrieve all sales records for “Bluetooth Speaker.” Then, it passes the revenue data from those records to the “Calculator” tool to sum the total. 00:14 The agent then provides a concise, accurate answer, explaining its methodology. This entire process occurs within the n8n environment, leveraging local data for fast and reliable responses. 00:24 n8n Data Tables n8n’s Data Tables feature provides a native, built-in database solution, eliminating the need for external databases or API calls for data storage and retrieval within your workflows. This is particularly advantageous for reducing latency and avoiding rate limits associated with external services. The data resides directly within your n8n instance. 01:20 You can access and manage your tables via the Data tables tab on the main n8n dashboard. Creating a New Data Table: 1. Navigate to the Data tables tab. 2. Click the dropdown next to “Create Workflow” and select Create Data Table. 01:40 3. Provide a name for your table. Upon creation, a new table includes three default columns which are managed automatically: id (a unique identifier for each row), createdAt, and updatedAt. 01:48

@Darvis Silk yes. I use google gemini to analyse video ask for give me timestamp