dbServices.js service, and you can view and manage the data directly from the Paige dashboard. The database is isolated per project, so tables and data in one project are never accessible to another.
What the database is used for
Your bot can store and retrieve any data it needs during conversations. Common use cases include:Contact profiles
Store names, preferences, and other details collected from contacts during conversations.
Conversation state
The system tables
contacts, conversations, and messages are maintained automatically to power the conversations dashboard.Booking and order data
Persist appointment bookings, order details, or service requests submitted via Flows or conversational intake.
Bot configuration
Store dynamic settings like business hours, menu options, or pricing that your bot reads at runtime.
System tables
Paige automatically creates and maintains three system tables in every project database:| Table | Description |
|---|---|
contacts | One row per unique phone number that has messaged the bot |
conversations | One row per conversation, linked to a contact; stores the current state |
messages | Every inbound and outbound message, linked to a conversation |
Creating and managing tables
You can create custom tables from the Database section of the dashboard or by asking the AI agent.From the dashboard
The dashboard lets you:- View all tables and browse their data
- Create a new table with custom columns
- Add columns to an existing table
- Insert, edit, and delete rows
- Clear all rows from a table
- Drop a custom table
Via the Code Agent
The Code Agent has full access to your database schema and can create and modify tables as part of building your bot. When you describe a feature that requires data storage, the agent will create the necessary tables before writing the bot code that references them. You can ask it to create tables, add columns, query rows, or seed test data — all in plain language, without leaving the chat.Supported column types
When creating tables, you can use the following column types:text, varchar, integer, bigint, numeric, boolean, date, timestamptz, uuid, jsonb, serial
Reading and writing from bot code
Your bot code connects to the project database automatically — no connection string or configuration required. The starter template includes a database service with pre-built helper functions for common operations (looking up contacts, recording conversations, inserting rows), and you can also write direct queries when you need more control. Ask the AI agent to write the database access code for you. For example:
“When a user submits the booking flow, save the booking to a bookings table with their name, service, date, and phone number.”
The agent will create the table if it doesn’t exist and write the code to insert the row.
Your bot code always connects to the same database visible in the dashboard. Any rows inserted by the bot appear immediately in the data browser, and any changes you make in the dashboard are visible to the bot on the next query.