Databases

Data tables turn your AI agent into a real business application that stores important information for your customers. Structured, persistent data, brings lasting power to your agent’s workflows.

What Are Databases?

Databases let your agent collect, store, and retrieve structured information across interactions. With simple Notion-style setup, you define the data tables and data fields for your agent. As the agent runs or your customer adds records, their database updates and powers their workflows and business outcomes.

Your databases are not centralized storage across all of your customers. You define the data structure, and then each customer has their own unique data.

Data control settings

You choose the level of exposure your customer’s have to the database:

• Level 1: Agent-Only Intelligence - Your database works behind the scenes. Customers experience smarter interactions without seeing tables.
• Level 2: Read-Only Transparency - Enable “Customers can view” to include data visualizations. Customers see their records and history, building trust through transparency.
• Level 3: Full Record Control - Enable “Customer can edit records” for true application functionality. Customers can add, update, and manage their own data.

Setting Up Your First Data Table

1. Navigate to Database in the build tab
2. Create a new table and give it a descriptive name

3. Add fields using the field types that match your data needs

4. Select the level of database control you want to provide your customers through database settings

   

5. Reference fields in your database into your agent instructions so the agent know how to relate to the data. Use @ mentions to show a list of your data tables and fields, or select the curly brackets in the text editor toolbar.

   

6. Preview your agent and notice the data tables appear below “New Interaction”

Remember: you can choose whether or not to expose the databases to your customers. Toggle the “Customers can view” setting to show/hide the tables.

When to use databases

Use databases any time your agent’s behavior or skills produce or utilize structured information.

Use Cases

For Consultants: Track client projects with fields for deliverables, deadlines, status, and notes. Your agent becomes a lightweight project management system that actually gets used.

For Coaches: Monitor client goals with progress percentages, milestone dates, and achievement checkboxes. Sessions become data-driven and outcomes trackable.

For Agencies: Manage content calendars with post titles, publish dates, platforms, and performance metrics. Your agent orchestrates the entire content workflow.

For Course Creators: Track student progress through modules, assignments, quiz scores, and completion rates. Personalized learning paths based on actual data.

Comparison to other features

Your Appy.AI agent has three types of data storage, each serving different purposes:

• The memory tool remembers behavioral patterns. For example, over many chats your agent learns that the customer prefers detailed explanations.
• Preferences configure static, personalized settings that your customers set in onboarding. For example, they define interests and freqency for a report the agent will produce.
• Databases are the ongoing business records produced by or provided to your agent. For example, one record for each sales lead captured and the information associated with that lead.

While memory captures conversation patterns for continuity and preferences store user settings for personalization, databases manage structured business data that powers real applications.

Getting Started

• Identify the business data your agent needs to track
• Create a data table and include the essential fields
• Configure visibility and permissions based on your use case
• @mention your database fields in your agent instructions
• Test with interactionsto discover additional fields you and your customers want to collect.

You’re on your way to giving your customers data that powers real business workflows and creates lasting value!