Empowering AI teams with seamless integration, rapid prototyping, and robust data handling through a serverless, RAG-as-a-Service platform.

Graphlit, an AI software provider, introduced the Graphlit Agent Tools Library, now live on GitHub (github.com/graphlit/graphlit-tools-python). This new toolkit builds on Graphlit’s RAG-as-a-Service platform capabilities, enabling developers to rapidly build AI agents that streamline data handling and LLM-driven workflows. By eliminating infrastructure complexities, Graphlit continues to position itself as a comprehensive solution for organizations seeking to harness large language models (LLMs) and unstructured data at scale.

“We are thrilled to introduce the Graphlit Agent Tools Library as a way to streamline the development of agent-driven AI applications,” said Kirk Marple, CEO of Graphlit. “By automating data ingestion, simplifying LLM integrations, and providing a rich set of ready-to-use tools, we’re enabling teams to turn unstructured data into high-impact AI-agent workflows faster than ever before.”

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Key Features and Benefits

  • Multi-Agent Orchestration
    Built-in CrewAI integration offers a streamlined path to multi-agent collaboration without heavy coding.
  • Extensive Data Connectivity
    Ingest data from Google Drive, OneDrive, Dropbox, SharePoint, Notion, Intercom, Zendesk, Slack, Teams, GitHub, Jira, Linear, and more, ensuring seamless integration of diverse sources into agentic workflows.
  • Robust RAG Tools
    Offers built-in capabilities for PDF OCR, content chunking, vector embeddings, and RAG conversation history in a single library of agent tools.
  • Multi-Model Compatibility
    Integrates with top LLMs (OpenAI, Anthropic, Cohere, Google AI, Groq, Mistral, etc.) for context-rich, near-real-time decision-making.
  • Multimodal Data Support
    Ingest and process diverse data types—including text, audio, video, and images—with automatic transcription and image embeddings for deeper AI insights.
  • Azure-Native Security
    Inherits enterprise-grade encryption, auto-scaling via Azure Functions, and compliance readiness (SOC 2, GDPR, HIPAA) from Microsoft Azure, ensuring robust governance for sensitive data at scale.

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Use Cases & Differentiators

  • Ease of Development, Production-Ready
    Quickly gain insights from web-based data, PDFs, audio recordings, videos, or images using batteries-included RAG tools and LLM integrations.
  • Customizable Workflows
    Ideal for competitor research, content generation, customer support, or code-related tasks—connect Slack, Intercom, or GitHub issues for targeted analysis.

Roadmap Highlights

  • Future Agent Framework Integrations
    Support for additional frameworks such as LangGraph and AutoGen, enabling even greater flexibility for orchestrating multi-agent systems.
  • User Memories
    Forthcoming support for both textual and graph-based “user memories,” enhancing contextual understanding over multiple agent interactions. Planned for release in January 2025.
  • Expanded Agent Authentication
    Hosted integrations with Microsoft, Google, and others to simplify credential storage and secure access at scale. Planned for release in Q1 2025.

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Source – PR Newswire

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