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AI SystemsFeatured Project

RulesForAI

A tool that transforms UI screenshots and text prompts into structured rules for AI coding tools like Cursor, GitHub Copilot, and others. It helps developers streamline their workflow by generating accurate, context-aware rules.

LLMOpenAIAutomationSaaS

Project Details

Client

Internal Product

Year

2024

Duration

3 months

Our Role

Full-stack Development & AI Integration

Key Result

Streamlined 50% of development time

Overview

Project Background

RulesForAI was born from a simple observation: developers spend countless hours translating design mockups and UI specifications into code. We built a tool that uses advanced AI to analyze screenshots and generate structured, context-aware rules that integrate seamlessly with popular AI coding assistants.

Technology Stack

Next.jsTypeScriptOpenAI APIVercelPostgreSQLTailwind CSS
The Challenge & Solution

Problem-solving approach

The Challenge

Traditional development workflows require manual interpretation of design specifications, leading to inconsistencies and wasted time. Developers needed a way to quickly generate accurate coding rules from visual references without losing context or precision.

Our Solution

We developed an AI-powered platform that processes UI screenshots using computer vision and natural language processing. The system extracts design patterns, component structures, and styling rules, then generates formatted output compatible with Cursor, GitHub Copilot, and other AI coding tools.

The Process

How we built it

A step-by-step breakdown of our development approach for this project.

01

Research & Discovery

Analyzed existing developer workflows and identified pain points in the design-to-code process. Interviewed 50+ developers to understand their needs.

02

AI Model Development

Trained and fine-tuned vision models to accurately identify UI components, layouts, and styling patterns from screenshots.

03

Platform Architecture

Built a scalable Next.js application with real-time processing capabilities and seamless API integrations.

04

User Testing & Iteration

Conducted beta testing with early adopters, iterating on feedback to improve accuracy and usability.

Results

Project Outcomes

Measurable results and impact from this project.

50%

Reduction in development time for rule creation

1000+

Active users within first month

95%

Accuracy rate in component detection

4.8/5

Average user satisfaction rating

RulesForAI has completely transformed how I work with AI coding assistants. What used to take hours now takes minutes.

S

Sarah Chen

Senior Developer at TechCorp