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Vector Tables (Beta)

October 2, 2024
Features

Overview:
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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:
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  • 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:
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  • 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:
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  • 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.

This release includes the vector-tables connector.