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Graphlit

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If you're building AI copilots, chatbots or other vertical AI apps, Graphlit simplifies and accelerates your development.

Compared to existing Open Source solutions like LangChain or LlamaIndex, which require the DIY combination of vector databases, LLM embeddings, cloud storage and data pipelines, our managed Graphlit platform handles your AI and data infrastructure for you.

No need to be limited by the OpenAI Assistants API - no file size limits (on all tiers), or storage limitations (on the Growth tier).

💸 Graphlit is free to use, up to 1GB of content, and paid plans start at $49/mo + credit usage.

💡 Signup today, and you can be ingesting data and having LLM conversations within minutes.

With integrated web scraping, Graphlit ingests existing websites by sitemap. With built-in audio transcription, it indexes podcasts, videos and meeting recordings. Any format of unstructured data will be made searchable, via metadata filtering and text and image embeddings. Slack, Notion, Google Mail and Microsoft Outlook email are supported as data feeds. Create automated LLM-generated alerts on people, places, companies or topics found in your content.

Use any content with RAG conversations, even images or websites described with the GPT-4 Vision model.

Example

from graphlit import Graphlit
from graphlit_api import *

graphlit = Graphlit()

await graphlit.client.ingest_uri(
  uri="https://www.graphlit.com"
)

response = await graphlit.client.prompt_conversation(
  prompt="How can Graphlit accelerate my Generative AI app development?"
)

message = response.prompt_conversation.message.message

print(message)

Accelerate your Generative AI app development

Features:

✅ API first: Made for app developers, not data scientists

✅ Graph-based: via LLMs, we build a knowledge graph from your unstructured data

✅ Multi-modal RAG: not just PDFs and web pages, we support audio, video and images

✅ Model-agnostic: we handle prompted retrieval with models from OpenAI, Anthropic, Meta, Mistral, etc.

✅ Managed cloud-native platform: fully automated unstructured data ETL pipelines

✅ No assembly required: no need for Langchain, Pinecone, S3, etc.

✅ Built-in multi-tenancy, semantic search, storage and workflow automation

✍️ Read more about use cases for Graphlit:

Try one of our sample applications

All sample applications can be found in our GitHub Repo.

🔥 Get started with our API documentation.

🆕 See our changelog for all the latest features.

We want to learn how we can help you build your AI apps faster with Graphlit.

Popular repositories Loading

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Repositories

Showing 10 of 15 repositories
  • graphlit-mcp-server Public

    Model Context Protocol (MCP) Server for Graphlit Platform

    TypeScript 48 MIT 4 0 0 Updated Mar 11, 2025
  • graphlit-client-typescript Public

    TypeScript client for Graphlit Platform

    TypeScript 0 MIT 0 0 0 Updated Mar 7, 2025
  • graphlit-client-dotnet Public

    .NET client for Graphlit Platform

    C# 0 MIT 0 0 0 Updated Mar 7, 2025
  • graphlit-client-python Public

    Python client library for Graphlit Platform

    Python 9 MIT 2 0 0 Updated Mar 7, 2025
  • graphlit-samples Public

    Sample applications built on the Graphlit Platform

    Jupyter Notebook 69 MIT 17 0 0 Updated Feb 26, 2025
  • ai-enablement-stack Public Forked from daytonaio/ai-enablement-stack

    A Community-Driven Mapping of AI Development Tools

    HTML 0 Apache-2.0 76 0 0 Updated Jan 14, 2025
  • graphlit-tools-python Public

    AI Agent Tools library for Graphlit Platform

    Python 17 MIT 1 0 0 Updated Jan 14, 2025
  • AgentStack Public Forked from AgentOps-AI/AgentStack

    The fastest way to build robust AI agents

    Python 1 MIT 155 0 0 Updated Jan 2, 2025
  • .github Public
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  • Jupyter Notebook 0 0 0 0 Updated May 6, 2024

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