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Mozaiks: Self-Hosted AI-Powered Multi-Tenant Web Application Runtime

Mozaiks is a self-hosted runtime environment for deploying AI-powered multi-tenant web applications, with built-in real-time UI, authentication, and billing features. Developers define applications via YAML and write agent logic using lightweight Python/JS code, focusing on business behavior rather than infrastructure.

AI应用多租户自托管运行时Web应用实时UI认证计费低代码
Published 2026-05-28 10:15Recent activity 2026-05-28 10:28Estimated read 6 min
Mozaiks: Self-Hosted AI-Powered Multi-Tenant Web Application Runtime
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Section 01

Mozaiks Guide: Core Introduction to Self-Hosted AI-Powered Multi-Tenant Web Application Runtime

Mozaiks is a self-hosted runtime platform developed by BlocUnited-LLC (Source: GitHub, Link: https://github.com/BlocUnited-LLC/mozaiks, Release Time: 2026-05-28T02:15:34Z) for quickly building and deploying AI-powered multi-tenant web applications. It addresses developers' pain points in infrastructure setup, with built-in real-time UI, authentication, billing, and other features. Through YAML configuration + lightweight code, developers can focus on business logic. It supports multiple scenarios and has obvious advantages compared to similar tools.

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Section 02

Project Background: Infrastructure Pain Points in AI Application Development

In current AI application development, developers spend a lot of time building infrastructure such as authentication, billing, and multi-tenant isolation, which prevents them from focusing on business logic and AI behavior design. Mozaiks provides an out-of-the-box complete runtime environment to specifically address this core pain point.

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Section 03

Core Features: Key Capabilities like Self-Hosting and Multi-Tenancy

  1. Self-hosting: Data sovereignty, privacy protection, cost control, customization, compliance-friendly
  2. Multi-tenancy: Tenant isolation, resource quota, custom domain, white-label support
  3. Real-time UI: Streaming response, interactive components, state management, responsive design
  4. Authentication: MFA, SSO integration, OAuth, RBAC, session management
  5. Billing: Usage metering, subscription management, Stripe integration, invoice generation, trial management
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Section 04

Development Experience: YAML Configuration + Lightweight Code + Workflow

  • YAML configuration-driven: Declaratively define application structure (app, AI models, UI components, etc.)
  • Lightweight code stubs: Write business logic (Agent class, tool functions) in Python/JS; the framework handles infrastructure
  • Workflow definition: Support multi-step complex processes (e.g., document processing: extraction → summarization → classification → notification)
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Section 05

Application Scenarios: Covering Multi-Domain AI Needs

Applicable scenarios: 1. AI SaaS products (intelligent customer service, content generation, etc.) 2. Internal AI tools (knowledge base Q&A, document processing, etc.) 3. AI Agent platforms (multi-agent collaboration, automated workflows) 4. Prototype validation (MVP development, A/B testing, proof of concept)

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Section 06

Technical Architecture and Deployment Options

  • Runtime components: API gateway, Agent executor, workflow engine, real-time service, tenant manager, billing service
  • Extensibility: Stateless services, message queue, Redis cache, PostgreSQL support
  • Deployment: Docker Compose (development), Kubernetes (production), bare metal, mainstream cloud platforms
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Section 07

Comparison with Similar Tools: Advantages of a Complete Solution

Compared with LangChain, Vercel AI SDK, and Dify: Mozaiks natively supports self-hosting, has built-in multi-tenancy/authentication/billing, and supports YAML configuration; LangChain requires building most functions by oneself, Vercel AI SDK lacks self-hosting/multi-tenancy, and Dify supports some but is not complete enough.

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Section 08

Conclusion and Recommendations

Conclusion: Mozaiks is a production-ready complete solution that abstracts infrastructure complexity, suitable for teams that value data sovereignty and multi-tenancy needs. Recommendations: Start with small-scale prototypes, use official templates, pay attention to community updates, and perform load testing before production. The future roadmap includes more model support, a visual editor, mobile SDK, etc.