Getting Started
Choose Your Path
Researchers & Scientists: Jump to Quick Start for 10-minute setup Cloud Users: Sign up at scrapalot.app - no installation needed! Developers: Check Architecture to understand the system
What is Scrapalot?
Scrapalot is a research intelligence platform that transforms documents into queryable knowledge:
Research-grade RAG
13 strategies, tri-modal fusion, knowledge graphs
Natural language queries
Ask complex questions, get synthesized answers with citations
Team collaboration
Shared workspaces, notes, and conversations
Academic integration
Direct import from Google Scholar, Semantic Scholar, arXiv
Privacy first
Self-host or cloud, you control your data
How It Works
- Upload or Connect - PDFs, EPUBs, Word docs, or link Google Drive, Dropbox, academic databases
- Ask Questions - Natural language queries across all your documents
- Get Insights - AI synthesizes answers from multiple sources with exact citations
Key Capabilities
For Researchers
Literature review acceleration
Query 50+ papers simultaneously
Citation tracking
Automatic source attribution and relationship mapping
Academic connectors
Import directly from Google Scholar, Semantic Scholar, arXiv
Knowledge graphs
Visualize relationships between concepts and papers
Collaborative notes
Team synthesis and discussion
For Technical Teams
Agentic RAG system
10+ perfectly crafted strategies and orchestrators with intelligent routing
Tri-modal fusion
Dense semantic (pgvector) + sparse lexical (BM25) + graph (Neo4j)
Context expansion
70% hallucination reduction through hierarchical document intelligence
17+ chunking strategies
Including Contextual Retrieval and Late Chunking
Multi-provider AI
OpenAI, Anthropic, Google, Ollama, local GGUF models
Full REST API
Programmatic access to all features
Prerequisites
Minimum Requirements:
- Node.js 18+ and npm (frontend)
- Python 3.12.8 (backend)
- PostgreSQL 14+ with pgvector extension (or SQLite for development)
Optional Components:
- Docker - Easier deployment
- Redis - Caching and session management
- Neo4j - Knowledge graph features
- GPU - For local model inference (NVIDIA CUDA or Apple Metal)
Next Steps
Quick Setup (10 minutes)
Quick Start Guide - Get running fast with minimal configuration
Learn the System
User Guide - Learn how to use Scrapalot Architecture - Understand the technical design 
Deployment - Deploy to production
Deployment Options
Desktop App (Free, Open Source)
- ✅ Complete source code (MIT licensed)
- ✅ Runs locally on your machine
- ✅ All agentic RAG strategies and research features
- ✅ Your data never leaves your computer
- ✅ Community support on GitHub
Best for: Individual researchers, students, privacy-first users
Cloud Researcher Plan (Free)
- ✅ Managed hosting - no setup
- ✅ Single-user workspace
- ✅ All research features
- ✅ Academic database connectors
- ✅ Generous usage limits
Best for: Researchers who want cloud convenience without infrastructure management
Professional & Enterprise (Paid)
Proprietary team collaboration code with deployment options:
- Professional - $19/mo managed cloud for small teams
- Enterprise - Deploy our code to your cloud infrastructure, custom pricing
Best for: Research teams, institutions, organizations requiring team collaboration
Getting Help
FAQ - Common questions answered GitHub Issues - Report bugs GitHub Discussions - Ask questions 
Email - support@scrapalot.com