Graphlit Unveils Agent Tools Library to Streamline Unstructured Data Ingestion and AI Agent Workflows
Empowering AI teams with seamless integration, rapid prototyping, and robust data handling through a serverless, RAG-as-a-Service platform.
SEATTLE, Dec. 31, 2024 /PRNewswire/ -- Graphlit, an AI software provider, today 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."
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.
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
- 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. - Future Agent Framework Integrations
Support for additional frameworks such as LangGraph and AutoGen, enabling even greater flexibility for orchestrating multi-agent systems.
Explore Graphlit Today
The Graphlit Agent Tools Library is now available on GitHub (github.com/graphlit/graphlit-tools-python). To explore Graphlit's serverless, RAG-as-a-Service platform at no cost, or to schedule a personalized demo, visit graphlit.com. Read more about building with agent tools on our blog (graphlit.com/blog/build-crewai-agents-with-graphlit-agent-tools).
About Graphlit
Unstruk Data, the developer of the Graphlit Platform, is a Seattle-based AI software company focused on simplifying the creation of intelligent applications and agents using unstructured data. As a serverless, batteries-included, RAG-as-a-Service platform on Azure, Graphlit manages data ingestion, vector embeddings, and LLM flows—allowing teams to build advanced AI solutions without the burden of complex data infrastructure. Follow us on X at @graphlit. Visit us at graphlit.com.
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SOURCE Unstruk Data Inc.