QuickCode - AI Microservices Generator

AI-Powered Diagram-Driven Microservices Generator

Describe your business requirements to AI, and QuickCode turns them into production-ready enterprise microservices deployed to the cloud.

Production-ready microservices from DBML, DSL, and AI-assisted design

CQRS or Service per module, regenerate safely without losing custom code

Gateway, identity, admin portal with live reports, and GitHub Actions deploy to Google Cloud Run

How it works

Illustration of building cloud microservices with QuickCode

DBML to Production Code

Draw your schema, add DSL annotations, QuickCode generates endpoints, handlers, and optimized Dapper SQL.

Safe Regeneration

Update your DBML and regenerate. Generated code updates while your custom logic stays untouched in partial classes. Built-in AI rule files keep generation behavior consistent across every regenerate.

Deploy to Cloud Run

Each project gets its own GitHub Actions pipeline deploying to Google Cloud Run, isolated builds, minimal setup.

Admin Portal

CRUD screens, live reports, group-based authorization, and table-level permissions — without writing a line of UI code.

Build Microservices with AI

Describe your system in plain language. QuickCode Studio analyzes it into modules, you review the plan, then each service schema is generated.

Iterative generation loop

Analyze, Design, Visualize, Code, Deploy

Run the same workflow again whenever you extend your system, with QuickCode.

Analyze

Design

Visualize

Code

Deploy

Explore a real project generated from DBML and DSL, including microservices, API gateway, identity, GitHub Actions pipelines, and cloud deployment configuration.

Inspect the generated source code, architecture, deployment pipeline, and project structure before you start building.

Explore Generated Repository

Extend your schema and regenerate as often as required, custom code remains protected across every update.

How QuickCode works, from your first AI prompt or DBML diagram through generated microservices, built-in gateway and identity, and automated deployment to production. When you add modules, tables, or fields, QuickCode updates your entire backend automatically, without breaking your custom code.

Create project with AI — AI project setup

Add module with AI — AI module generation

QuickCode Studio workspace — Studio workspace

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.

Extend Generated Code

Use partial classes and your own files for custom behavior. QuickCode regenerates .g.cs scaffolding, it does not overwrite the code you added.

Regenerate Without Starting Over

Update tables, DSL, or modules in Studio, then regenerate. New APIs and migrations land while your extensions stay in place and keep compiling.

Real APIs from Day One

Working endpoints with Dapper and real database operations, not empty Swagger mocks.

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.

GitHub Actions pipeline run — Deploy pipeline

Generation pipeline in Studio — Studio pipeline

GitHub & Cloud Run

Generated code is pushed to GitHub under QuickCodeNet/{project-name}. GitHub Actions build containers and deploy to Google Cloud Run, gateway, portal, and module APIs.

GitHub

Cloud Run

See the Full Walkthrough

This is the short version. For every step (from project setup and Studio to generation pipelines and the live demo) open How It Works or try the demo from the menu.

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.

Entry points: Admin users use the portal; external systems call APIs through the gateway (YARP).
Identity: Central authentication service and dedicated identity store for users, groups, and tokens.
Generated services: One deployable API per module, each with an isolated database (no cross-module DB coupling).
Events: Kafka-backed listener coordinates workflows and cross-service reactions without tight synchronous coupling.
Observability: Logs and metrics flow into Elasticsearch/Kibana for operations and troubleshooting.
Delivery: Generated repos include CI/CD (e.g. GitHub Actions) toward container runtimes such as Google Cloud Run.

The diagram shows component types and data flow, not individual module names from a sample project.

QuickCode reference microservices architecture diagram