# Vector Tables (Beta)

\*\*Overview:\*\*Vector Tables introduce a seamless way to store and process vector embeddings directly within the Tray.ai platform. This new capability is a core component Chatbots, AI Assistants, Agents, RAG pipelines, and most other AI Applications. Make AI trustworthy with Vector Tables by grounding your it with your proprietary and up-to-the-minute data.

**Key Features:**- **Integrated Vector Storage:** Store, manage, and query vectors directly in Tray.ai to enable AI-powered workflows and applications.

* **High-Performance Search & Retrieval:** Efficiently retrieve and compare vector-based data, allowing for quick similarity searches and enhanced AI functionalities.
* **Enhanced AI Workflows:** Unlocks the power of AI by allowing models to access a wider range of data, enhancing applications like chatbots, personalized recommendations, and semantic search.

**Benefits:**- **Rapid AI Implementation:** Build and deploy AI solutions faster without needing additional vector-specific tools or databases.

* **All-in-One Platform:** Manage your vector data securely within Tray.ai, streamlining the process of building AI-driven services and automations.
* **Improved Data Security:** Vector Tables are stored securely in Tray-owned databases, with no data leaving the platform, ensuring compliance with security and governance standards.

**Use Cases:**- **Chatbots Leveraging Company Knowledge:** Deploy AI chatbots (e.g., on Slack) that can access your company’s data for:

* Sales teams creating high-quality follow-ups.
* IT teams to automatically resolve common support tickets.
* Customer success teams to streamline communication with customers.

[Learn more in our documentation on the feature.](https://tray.ai/documentation/platform/automation-integration/advanced-capabilities/vector-tables)

This release includes the `vector-tables` connector.