They act as lightweight, AI-friendly databases that Agents can read from and write to — supporting structured workflows such as contact registration, lead tracking, unresolved inquiries, and feedback collection. A Table can be fully managed inside the Builder interface, with tools for creating, editing, and linking it to one or more Agents.
🧩 Core Concepts
| Concept | Description |
|---|---|
| Table | A dynamic dataset used by Agents to store or retrieve information. |
| Columns | Define the structure of your Table — similar to database fields. |
| Rows | Each entry or record in your Table. |
| Semantic Search | A feature that allows Agents to query data using meaning and context, not only keywords. |
💡 Why Tables Matter
Tables extend your Agents’ memory and logic capabilities by providing:- Persistent storage — Agents can log user interactions or unresolved questions.
- Structured intelligence — Data can be filtered, queried, and reasoned upon.
- Collaboration — Shared datasets can be used across multiple Agents or Squads.
- Automation — Tables integrate seamlessly with workflows, triggers, and tools.
- “Unanswered Questions” log for training or review.
- “Contacts” table for lead management.
- “Feedbacks” table for quality tracking.