Context engineering for developers.
Ingest any content, extract what matters, give your AI the memory it needs.
Graphlit is a cloud-native platform that gives AI applications semantic memory. Not just vector search – real knowledge retrieval with context, relationships, and understanding.
One API for the complete stack: content ingestion, extraction, enrichment, storage, and retrieval.
import { Graphlit } from "graphlit-client";
const client = new Graphlit();
// Ingest and automatically extract entities, relationships
await client.ingestUri("https://example.com/report.pdf");
// Semantic search across all your content
const results = await client.queryContents({
search: "Q4 revenue concerns enterprise pricing"
});
// Chat with your data using RAG
await client.streamAgent(
"What are the key pricing concerns from enterprise customers?",
(event) => console.log(event.message)
);
Building semantic memory is hard. Maintaining it in production is harder.
Typical Solutions | 🚀 Graphlit |
---|---|
Just vectors – no semantic memory | Semantic memory platform |
Basic pipelines | Complete ingestion-to-retrieval stack |
Limited multimodal or text-only | True multimodal from day one |
New to production | Years of production hardening |
Save weeks of engineering time. Skip the infrastructure. Ship features, not glue code.
- Documents: PDF, DOCX, PPTX, Excel, Markdown
- Media: Audio transcription, video processing, image analysis
- Web: Scraping, RSS feeds, sitemaps
- Platforms: Slack, Gmail, Notion, GitHub, Jira, Linear, SharePoint, and more
- Cloud Storage: S3, Azure Blob, Google Drive, Dropbox, OneDrive, Box
- Entity recognition and linking
- Relationship mapping
- OCR and visual object detection
- Audio transcription with speaker diarization
- Automated summarization
- Semantic search (vector + hybrid)
- Knowledge graph queries
- RAG-powered conversations
- Multi-tenant filtering
- Context-aware results
OpenAI • Anthropic • Google • xAI • Deepseek • Groq • Mistral • Cohere • Cerebras • AWS Bedrock
All models support tool calling, streaming, and reasoning modes.
Connect Graphlit to your favorite AI coding tools:
Cursor • VS Code • Windsurf • Claude Desktop • Claude Code • ChatGPT
npx -y graphlit-mcp-server
- TypeScript/JavaScript –
npm install graphlit-client
- Python –
pip install graphlit-client
- C# / .NET –
dotnet add package Graphlit.Client
- 📖 Documentation – Complete API reference and guides
- 🎥 YouTube Channel – Video tutorials and demos
- 💬 Discord Community – Get help and share ideas
- 🌐 Website – Platform overview and pricing
- Sample Apps – Production-ready examples
- MCP Server – Model Context Protocol integration
Free tier includes:
- ✓ 1GB storage • 1K content items • 3 feeds • 100 conversations
- ✓ All content types (PDFs, audio, video, web pages)
- ✓ Full API access
- ✓ Community support
No credit card required. No infrastructure to manage.
- AI Agents & Copilots – Give your AI memory and context
- Knowledge Management – Build searchable repositories from unstructured data
- Document Intelligence – Extract insights from PDFs, reports, contracts
- Customer Support – RAG-powered chatbots over your documentation
- Research Tools – Semantic search across academic papers, articles
- Media Analysis – Transcribe and analyze audio/video content
- Content Platforms – Automated ETL for LLM training data
- Multi-tenant architecture with RBAC
- Encrypted at rest and in transit
- Usage-based pricing – pay only for what you use
- Serverless – no infrastructure to deploy
- SOC 2 & SLA available on Growth tier (Coming Soon)
Get Started Free • Read the Docs • Join Discord
Built by developers, for developers. 🚀