Shinrag Overview
Shinrag is a comprehensive, all-in-one platform designed for building and deploying intelligent agents powered by Retrieval-Augmented Generation (RAG) technology. It empowers developers and teams to create AI systems that can understand and interact with their private data, such as documents, FAQs, and knowledge bases. The platform's core is its Visual Pipeline Builder, a no-code, drag-and-drop interface that simplifies the creation of complex, multi-agent workflows. This allows users to connect different AI agents, implement conditional routing based on confidence scores, and synthesize information from multiple sources without writing extensive orchestration code. Shinrag handles the entire RAG lifecycle, from data uploading and vectorization to agent creation and API deployment, making it a fast and scalable solution for building applications like internal knowledge bases, intelligent support assistants, and sophisticated automation tools.
How to use Shinrag
Shinrag simplifies the process of creating intelligent agents into three main steps: 1. Upload Your Data: Begin by uploading your documents, JSON, or CSV files to the platform. Shinrag automatically processes, embeds, and indexes your content for efficient semantic search. 2. Create Agents & Pipelines: Configure individual AI agents, assigning specific datasets to each. Then, use the Visual Pipeline Builder to connect these agents, add conditional logic, and create multi-stage workflows. 3. Query & Deploy: Once your pipeline is built, you can start asking questions through the web interface or integrate it into your applications using the provided REST API. The system provides accurate, context-aware answers complete with source citations.
Core Features of Shinrag
- Visual Pipeline Builder: A drag-and-drop interface to build, test, and deploy complex multi-agent RAG workflows without writing code.
- Intelligent Agents: Create context-aware AI agents that provide accurate answers based on your specific datasets.
- Dataset Management: Easily upload, manage, and embed various data formats (documents, JSON, CSV) with automatic vectorization.
- Multi-Agent Orchestration: Chain multiple agents in parallel or sequential workflows, with conditional routing to handle complex queries.
- Synthesis Nodes: Intelligently combine and rank results from multiple agents to provide a single, comprehensive answer.
- Semantic Search: Utilizes advanced vector search for fast and relevant information retrieval across all your data.
- Developer-Friendly API: A full-featured RESTful API allows for seamless integration into existing applications and workflows.
- Security & Privacy: Enterprise-grade security ensures your data remains private, with full control over your API keys and models.
Use Cases for Shinrag
Shinrag is ideal for building a variety of AI-powered applications. A primary use case is creating internal knowledge bases that unify scattered documentation from sources like Confluence, GitHub, and Slack, allowing teams to find answers instantly. It can also be used to build intelligent customer support assistants that answer user queries based on product docs, troubleshooting guides, and billing FAQs. For more complex needs, developers can automate multi-stage data processing workflows, synthesize research from multiple documents, and create specialized agents for different business domains like engineering, product, and HR.
Advantages of Shinrag
The main advantage of Shinrag is its ability to drastically reduce the time and complexity of building production-ready RAG systems, from weeks to just hours. Its no-code visual builder democratizes AI development, allowing non-experts to create sophisticated pipelines. The all-in-one nature of the platform eliminates the need to integrate and manage separate vector databases, embedding APIs, and orchestration logic. It is built for performance, offering fast and scalable retrieval, and provides a secure environment where users retain full control over their data and models. The platform is also highly flexible, supporting custom LLM models and providing robust API access for developers.
Pricing and Plans
Shinrag offers a tiered pricing structure to accommodate different needs:
- Free Plan: $0 for a 3-day trial, including 10K tokens, 1 dataset (up to 10 MB), 1 agent, and 1 pipeline with up to 3 nodes. Ideal for testing the platform.
- Developer Plan: $39 per month, designed for individual developers. It includes 1M tokens, 5 datasets (up to 100 MB), 5 agents, 3 pipelines with up to 10 nodes per pipeline, and API access.
- Developer Plus Plan: $149 per month, aimed at growing teams. It offers 5M tokens, unlimited datasets (up to 1 GB storage), unlimited agents, unlimited pipelines, and unlimited nodes per pipeline.
For all plans, token limits apply to platform-provided API keys, but users can connect their own API keys to bypass these limits.
Shinrag FAQ
Traffic
Latest traffic
Status
Monthly traffic trend
- 2026-1: 0
- 2026-2: 98
- 2026-3: 2.0K
- 2026-4: 2.4K
- 2026-5: 3.4K
Geography
Top 5 countries / regions
- 🇲🇳Mongolia56.3%
- 🇲🇲Myanmar (Burma)32.6%
- 🇺🇸United States11.2%
Top keywords
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