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Getting Started

Complete guide to building AI-powered workflows with RAPFlow

RAPFlow is a powerful visual workflow builder that enables you to create sophisticated AI-powered document processing and automation flows. It is not only an AI solution builder but also supports fine-tuning ML models and building agentic flows. With an intuitive drag-and-drop interface and a comprehensive set of pre-built blocks, you can build complex workflows without writing code.

What You'll Learn

This documentation covers everything you need to know about RAPFlow:

Key Features

  • Visual Flow Builder: Drag-and-drop interface for creating complex workflows
  • AI-Powered Blocks: Pre-built components for document processing, OCR, classification, and more
  • Flexible Integration: Connect with various data sources and external services
  • Real-time Processing: Execute workflows with live data and immediate results
  • Scalable Architecture: Built to handle enterprise-level document processing needs
  • Human-in-the-Loop: Built-in validation system for ensuring accuracy and quality

Getting Started

The best way to get started is to jump into the Building Flows guide, which will walk you through creating your first workflow in the Flow Editor.

For a complete reference of all available components, check out the Blocks Reference section.

Core Concepts

RAPFlow is built around several key concepts that make it powerful and flexible:

Blocks (Nodes)

The fundamental building blocks of a flow. Each block performs a specific function, from simple data manipulation to complex AI operations.

Messages

Data that flows between blocks in the form of JavaScript objects, typically containing a payload property with the main data.

Flows

Organized sets of connected blocks that work together to accomplish a specific task or process.

Context

A mechanism for storing and sharing information between blocks without using messages.

Human Validation

Built-in support for human review and validation of AI-generated results through the verify_me block.

  • Document Processing: Extract, classify, and process various document types
  • Invoice Automation: Automatically extract data from invoices and validate with human oversight
  • Content Classification: Categorize documents and content automatically
  • Data Extraction: Pull structured data from unstructured documents
  • Quality Assurance: Implement human-in-the-loop validation for critical processes