Explore a real generated project — microservices, gateway, identity, GitHub Actions, and cloud deploy config — before you start building.
Explore Generated RepositoryAI-Powered Microservices Development Platform
Design your system with AI, generate production-ready services, orchestrate business workflows, and deploy — while keeping architecture, code and documentation in sync.
- AI analysis with versioned project and module contexts
- DBML/DSL first, then workflows from the same analysis
- Ask Your Project on analysis, contexts, and DBML with edits via diff
- Generate per module (.NET or Node.js), deploy, regenerate safely
Start from a prompt
We’ll draft modules and open questions, then refine the plan with you. Generate the stack when it’s ready.
How you build with QuickCode Studio
Describe and analyze, ask about the plan, shape schema and workflows, then generate per module and deploy.
Describe & analyze
Write a brief (optional PDF). AI builds a project analysis plus a separate analysis and context for each module. Versions are saved so you can reopen and reanalyze.
Ask Your Project
Ask about analysis, contexts, architecture, and DBML. QuickCode AI can change the schema with confirm → diff → save, and guide new workflows.
Schema & DSL
Generate DBML from the plan or edit by hand. Tables get CRUD; QuickCode DSL in Notes becomes custom REST endpoints. DBML is versioned.
Workflows after DBML
Analysis suggests business flows early. After DBML exists, create Kafka or endpoint workflows yourself or with AI. Each workflow is versioned and deployable.
Generate & regenerate safely
Per module: .NET or Node.js, Service or CQRS, SQL Server, MySQL, or PostgreSQL. Change later, regenerate; your custom code stays.
Deploy on Cloud Run
Watch GitHub Actions and Cloud Run in QuickCode Studio as gateway, portal, and module APIs go live together.
Continuous Improvement
Analyze → Schema → Workflows → Generate → Deploy
Review the plan in QuickCode Studio, refine DBML and workflows, then ship and loop back anytime.
AI-Powered DBML Generation
Describe your business requirements in plain language or edit DBML in QuickCode Studio. AI (Gemini, OpenAI, Claude) proposes modules and schemas; you refine tables, relationships, and QuickCode DSL before generation.
Google Gemini
OpenAI
Anthropic Claude
Why QuickCode is Different
QuickCode ships a full generated codebase, not one-off AI snippets. Add your own endpoints, services, and business logic on top; when you change DBML and regenerate, the fresh generated layer and your additions still work together.
Regenerate Without Breaking Your Code
Update tables, DSL, or modules in QuickCode Studio, then regenerate. New APIs and migrations land while your custom code in partial classes stays in place and keeps compiling, no manual merges.
Consistent Architecture
Every generated service follows the same patterns for logging, validation, auth, and CI/CD, so a new module looks like the ones your team already knows.
Real APIs from Day One
Working endpoints with Dapper and real database operations, not empty Swagger mocks.
AI Rule Pack (Persistent)
Every project ships AI guide files (AGENTS.md, CLAUDE.md, Cursor rules, Copilot instructions) that tell assistants where generated code ends and your code begins. Regeneration preserves them, so AI keeps following your project rules.
DBML, DSL & APIs
Every table gets automatic CRUD. In DBML table Notes, QuickCode DSL adds custom Query (read), Update, and Delete operations, each line becomes a REST endpoint with handlers and Dapper SQL.
Query, Update, Delete in Notes
Query: filters, joins, reports, and existence checks. Update: named state changes (e.g. mark paid, reduce stock). Delete: conditional or bulk deletes beyond delete-by-id CRUD.
CQRS or Service
Choose CQRS + Mediator or Service architecture per module.
Full Microservices Stack
Every project includes per-module APIs, YARP gateway, admin portal, and IdentityModule, users, roles, and permissions without duplicating auth modules in your DBML.
A Complete Admin Portal, Generated as Source Code
More Than CRUD: Media & Live Reports
More Than CRUD: Media & Live Reports
The admin portal is generated as MVC source code in your project — not a hosted QuickCode SaaS panel. It goes past table forms: declare BLOB_IMAGE, BLOB_PDF, BLOB_VIDEO, or BLOB_FILE columns in DBML and get upload fields, list actions, and in-app preview. DSL Query operations become Live Reports with parameters, a result grid, and PDF/CSV export.
File & media columns
Image lightbox, PDF iframe, and HTML5 video preview without custom UI code. Files are stored as HTTPS object URLs on Azure Blob, any S3-compatible provider such as Cloudflare R2, or local disk in development, never as binary in the database.
Live Reports with Print & export
Set parameters, run the report, and see the matching GET API path on the page. Print & export lets you choose columns, set widths, reorder fields, then download PDF/CSV.
GitHub & Cloud Run
Generated code is pushed to GitHub under QuickCodeStudio/{project-name}. GitHub Actions build containers and deploy to Google Cloud Run, gateway, portal, and module APIs.
GitHub
Cloud Run
Ask Your Project
After your project is analyzed, ask questions about architecture, modules, the data model, business rules, and APIs. QuickCode AI answers using the project structured context — not generic assumptions. QuickCode does not just generate your project. It understands it.
Grounded in your project
Answers use the Project SOT, module SOTs, module dependencies, DBML, DSL business rules, and generated APIs.
Example questions
Which modules are affected if I change this table? How does authentication flow through this project? Where is customer status used? Which APIs depend on this module?
Microservices Architecture
Platform overview
QuickCode targets a modular microservice layout: each bounded context becomes an API with its own database, fronted by a single gateway and optional admin UI, not a monolith with shared tables.
- Gateway & portal: External APIs via YARP; admin users use the generated portal.
- Isolated services: One deployable API and database per module, plus central identity.
- Events: Kafka-backed listener service coordinates async workflows across modules.
- Observability: Gateway health checks plus logs and metrics in Elasticsearch/Kibana.
- Delivery: Generated CI/CD (e.g. GitHub Actions) toward runtimes such as Google Cloud Run.