CANVAS01 / 06
Visual Pipeline Builder
Connect document, retrieval, model, and output stages on one interactive graph.
Visual RAG development
Build RAGworkflows,visually.
Design, connect, configure, and validate retrieval-augmented generation pipelines in one intuitive workspace.
100%basichybrid
↳Document Loader
input · files
◇Retriever
dense search
✧Hybrid Retriever
dense + BM25
⇢Answer / Output
final stage
TEMPLATE PATHS · DEMO
01Basic RAG7 nodes ✓
02Hybrid Search8 nodes ✓
UIDesign previewNo execution
●10 configurable nodes
●Template path ·Basic RAG
What is Ragify?
From disconnected steps to one visual workflow.
Ragify brings document loading, chunking, embeddings, retrieval, and answer generation intoone connected workspace.See how each stage fits together, tune the components, and understand the graph you build.
Core features
Build withclarityat every step.
CONFIGURE02 / 06
Configurable Components
Open a node to shape its settings, from chunking to retrieval and generation.
TEMPLATES03 / 06
Starting Templates
Choose Basic RAG or Hybrid Search, then make the workflow your own.
NODE LIBRARY04 / 06
Ten Focused Nodes
Explore loading, chunking, embedding, storage, retrieval, reranking, output, and evaluation.
VALIDATE05 / 06
Graph Validation
Spot incomplete connections and configuration issues before moving forward.
GET STARTED06 / 06
Guided Onboarding
Choose your use case and arrive at an editable starter graph in a few steps.
How it works
Your workflow,three simple steps.
01 / CHOOSE
Choose a starting point.
Start with Basic RAG for a focused retrieval flow, or Hybrid Search for a richer strategy with reranking.
01 / 03
TEMPLATE SELECTION · PREVIEW
02 / BUILD
Connect and configure.
Arrange nodes on the canvas and set the options that shape how each stage works.
02 / 03
PIPELINE EDITOR · ILLUSTRATION
↳Loader
✧Chunker
◇Retriever
↗Answer
Node settings shape each stage⚙
03 / VALIDATE
Validate your workflow.
Review structural and configuration feedback, address issues, and refine the graph with more confidence.
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VALIDATION FEEDBACK · EXAMPLE
✓Pipeline review
An example of the editor's graph checks
✓
ConnectionsGraph structure reviewed
CHECK✓
Output stageAnswer node present
CHECK!
Node configurationReview the highlighted setting
REVIEWThe Ragify Experience
Build visually today.
More to come.
Explore the visual foundation of Ragify and the capabilities planned for the complete platform.
Visual Builder
Design and connect the building blocks of a RAG workflow on a visual canvas.
- Interactive pipeline canvas
- Connect and edit nodes
- Basic RAG and Hybrid Search templates
- Graph editing with undo/redo
Configure & Validate
Adjust individual pipeline stages and review configuration feedback before moving forward.
- Node-specific configuration forms
- Document, retrieval, and model-stage controls
- Graph and configuration validation
- Guided four-step onboarding
Deploy & Integrate
The next phase of Ragify is designed to take visual workflows into running applications.
- Persistent pipeline saving
- Backend document ingestion and execution
- Pipeline deployment
- API keys and external application integration
FAQ
Questions,
answered.
A few useful things to know before exploring Ragify.
Ragify is a visual environment for designing and configuring retrieval-augmented generation (RAG) pipelines. It helps you connect document processing, retrieval, and answer-generation stages in one workspace.
You can build and configure supported workflows through Ragify’s visual editor without writing the pipeline structure by hand. Familiarity with RAG concepts is still useful when choosing node settings and retrieval strategies.
A RAG pipeline prepares information, retrieves relevant context, and passes it to a language model to help produce grounded answers. Ragify represents these stages as configurable, connected nodes.
Basic RAG uses a dense retrieval stage. Ragify’s Hybrid Search template combines semantic and keyword-based retrieval and adds a reranking stage.
The editor includes Document Loader, Chunker, Embedder, Vector Store, Retriever, Hybrid Retriever, Reranker, LLM, Answer / Output, and RAGAS Evaluator nodes.
The current frontend lets you select supported document types, including PDF, DOCX, TXT, CSV, and Markdown. This is a metadata-only preview: document ingestion, processing, and storage are not yet connected to a backend.
Ragify currently provides frontend graph and configuration validation. Pipeline graphs are session-only, and backend execution and persistent saving are not available yet. A validation success does not mean the workflow has run.
External chatbot integration through deployed pipeline endpoints and API keys is part of Ragify’s planned platform. The current API Access interface is a preview; operational endpoints and keys are not available yet.
Pricing has not been finalized or announced. The cards on this page describe current frontend-preview capabilities and planned functionality, not paid subscription plans.
Start your first workflow
Ready to build your firstRAG workflow?
Start with a template, customize the steps, and bring your RAG workflow into focus.