ℹ️ About AgentVectorDB (AVDB)

Overview

AgentVectorDB (AVDB) is a flagship open-source project by Superagentic AI (opens in a new tab), designed to revolutionize how AI agents store, retrieve, and manage their cognitive states. Built as a specialized layer on top of LanceDB, it provides optimized memory management capabilities specifically for AI agents.

💡 Built on LanceDB

AgentVectorDB (AVDB) is not a competitor to LanceDB, but rather extends its capabilities for AI agent use cases. We share the same Apache 2.0 license and build upon LanceDB's robust foundation.

About Superagentic AI

Superagentic AI (opens in a new tab) is a pioneering company dedicated to building cutting-edge AI agent tools and software. Our mission is to enable safer, smarter agentic systems through Agent Experience (AgentEx) for businesses.

Our Focus

  • Agent Experience (AgentEx):

    • Developing tools that enhance AI agent interactions
    • Optimizing agent memory and cognition
    • Creating seamless agent workflows

  • Safety-First Approach:

    • Building reliable, secure infrastructure
    • Implementing ethical AI principles
    • Ensuring data privacy and security

  • Business Integration:

    • Enterprise-ready solutions
    • Scalable agent deployments
    • Production-grade reliability

Project Leadership

Core Team

Technical Architecture

Built with Modern Stack

  • Vector Operations:

    • LanceDB core integration
    • Optimized similarity search
    • Efficient vector indexing

  • Python Ecosystem:

    • Python 3.8+ compatibility
    • AsyncIO integration
    • Type hints support
    • Modern coding patterns

  • Enterprise Features:

    • Async-first architecture
    • Production-grade security
    • Scalable infrastructure
    • Monitoring capabilities

Key Features

  • Memory Management:

    • Optimized for agent cognition
    • Contextual memory retrieval
    • Importance-based scoring
    • Memory pruning strategies

  • Vector Operations:

    • High-performance search
    • Batch processing support
    • Custom embedding support
    • Efficient indexing

  • API Support:

    • Async/sync interfaces
    • RESTful endpoints
    • WebSocket support
    • SDK integration

Development Philosophy

Core Principles

  1. Agent-First Design

    • Optimized for AI agents
    • Cognitive architecture support
    • Natural interaction patterns

  2. Performance Focus

    • Speed optimization
    • Resource efficiency
    • Scalability built-in

  3. Developer Experience

    • Intuitive APIs
    • Comprehensive docs
    • Example-driven learning

Open Source Commitment

AgentVectorDB is proudly open source, released under the Apache-2.0 license. We believe in:

  • Transparent Development:

    • Public roadmap
    • Open discussions
    • Community feedback

  • Community Collaboration:

    • Shared knowledge
    • Collective improvement
    • Educational resources

  • Ethical AI Development:

    • Responsible AI practices
    • Safety considerations
    • Ethical guidelines

Contributing

Ways to Contribute

  1. Code Contributions

    • Feature development
    • Bug fixes
    • Performance improvements

  2. Documentation

    • Technical writing
    • Example creation
    • Tutorial development

  3. Community Support

    • Issue triage
    • Question answering
    • Use case sharing

Community & Support

Connect With Us

Enterprise Solutions

For professional support:

Email: enterprise@super-agentic.ai
Website: https://super-agentic.ai
Support: https://super-agentic.ai/support

Citation & Recognition

Academic Citation

@software{agentvectordb2024,
  title = {AgentVectorDB: The Cognitive Core for AI Agents},
  author = {Jagtap, Shashi and {Superagentic AI}},
  year = {2024},
  url = {https://github.com/superagenticai/agentvectordb},
  organization = {Superagentic AI}
}

Special Thanks

  • LanceDB Team for the foundational technology
  • Open source contributors
  • Early adopters and testers

Built with ❤️ by Superagentic AI