Get started

Quickstart

Get up and running with Sheeta AI in under 5 minutes. This guide walks you through connecting your first database, setting up tables with existing data, and generating insights.

If you haven't installed Sheeta AI yet, download it and complete the installation before continuing.

Open a Project

Choose one of the following methods to get started with a project in Sheeta AI.

Cloning a project helps you get started quickly with your team's existing work. This feature requires Git to be installed on your device. If you don't have Git installed, you can download it or choose the Start from Scratch method instead.

  1. Open the Sheeta AI application.
  2. Click Clone repo.

  3. In Repository URL, paste the following:

    https://github.com/Sheeta-AI/sample-ecommerce.git
  4. In Destination Folder, select where you want to store the project.
  5. Click Clone to download the project.
Sheeta AI clone project

You now have a project with pre-configured connections and sample data.

Set Up a Local Database

Skip this section if you already have a PostgreSQL database running on your machine.

DBngin is a free application that simplifies managing local databases.

  1. Download and install DBngin.
  2. Click the + button and select PostgreSQL.
  3. Choose your preferred PostgreSQL version and click Create.
  4. Click Start to run the database.
  5. Your default database credentials are as follows:
    • Username: postgres
    • Password: (leave it blank)
DBEngin screenshot

Connect to the Database

Follow these steps to add the connection:

  1. Click the edit icon next to the first connection dropdown.
  2. If you cloned the sample project, select the existing Development connection and update the username and password .
  3. If you started from scratch, click Add connection, select Postgres, and fill in the connection details.
    • Connection Name: Development
    • Host: localhost
    • Port: 5432
    • Database Name: postgres
    • Username: (depends on your Local DB setup in the previous step)
    • Password: (depends on your Local DB setup in the previous step)
  4. Click Test Connection to verify everything works.
  5. Click Save.
Database connection settings

Import Data

Now let's import the sample data into your database.

  1. On the left side panel, click Import data.
  2. Choose purchases.csv from the dataset folder.
  3. Review the column preview and click Preview.Data import complete
  4. Review the data preview and click Import.
  5. Wait for the import to complete. You can click "View" button on the notification popup on the buttom right of the screen to show file importing progress.Data import complete

Once complete, the new table appears in the database panel. Click on it to preview the data.

Data import complete

Explore Your Data

Let's find the oldest purchases for book products using the built-in sorting and filtering tools.

  1. In the data preview for the purchases table, scroll to the purchase_date column.
  2. Click the sort toggle once to sort by purchase_date in ascending order.
  3. Scroll to the product_category column and click the filter icon.
  4. Check Books to filter the results.

You now see a list of book product purchases sorted by oldest order date—no SQL required.

Data exploration with filters

Generate Insights with AI

Let's use the AI assistant to analyze monthly sales trends forbook products—without exposing sensitive customer information to the AI.

  1. Click the infinity icon at the top right corner (or press Cmd+I) to open the AI agent panel.
  2. Tip: Hide the left panel by clicking the toggle at the top left (or press Cmd+B) for more space.
  3. If you haven't logged in yet, click Login and complete the sign-up process.
  4. Send this message: What is the trend of monthly book product sales?
  5. When prompted for column permissions, select only: purchase_date, product_category, and total_purcahse_amount. Check Save Settings to remember these preferences.AI-generated insights
  6. The AI generates a query to analyze book sales trends. Notice that while the AI recorrects itself to find the extact Books category in the product_category field. The AI can't access any customer information in the table. It explains sales trend based on data.AI-generated insights
  7. SQL queries generated by the AI agent can be viewed by clicking at. The app shows the full query and you can run it to see the full result.AI-generated insights

Note: AI query limits depend on your account tier. To increase your limit, upgrade to Plus or Pro.