🧠 Ingest & Vectorize in 1 Round-Trip

Web Data Extraction for Enterprise RAG Pipelines

Transform live websites and documentation into semantic Markdown chunks and native 1536-dim or 3072-dim vector embeddings directly for Pinecone, Qdrant, Milvus, and pgvector.

Build Better RAG Free → LangChain & LlamaIndex
RAG Ingestion with Native Embeddings 
curl -X POST https://api.flycrawl.net/api/v1/scrape \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://docs.python.org",
    "formats": ["markdown", "chunks", "embeddings"],
    "embeddings": {
      "model": "native-large",
      "dimensions": 3072
    }
  }'