Contributed as a Backend Developer to an interdisciplinary university-industry project focused on automating mobile app creation for small and medium-sized enterprises (SMEs). The platform generates fully populated app concepts within minutes by collecting publicly available business information, analyzing it using AI, and transforming the results into structured application content.

Users can select a business through an interactive map interface or provide a website URL, after which the platform automatically gathers relevant information and generates a customized app preview, significantly reducing the manual effort typically required during the early stages of app development.

Overview

The project combines large-scale data acquisition, AI-assisted content generation, and real-time content delivery into a unified workflow. By automating the collection and transformation of business information, the platform demonstrates how modern AI systems can accelerate digitalization processes for small and medium-sized companies.

As part of the backend team, I was responsible for designing and implementing core systems responsible for data extraction, AI processing, performance optimization, and service integration.

Automated Data Acquisition

Developed backend services responsible for collecting and normalizing publicly available business information from multiple online sources.

Responsibilities included:

• Website crawling and content extraction
• Structured data parsing
• Business information normalization
• Data quality validation
• Integration of map and location-based services

The resulting pipelines transformed heterogeneous web content into consistent data structures suitable for downstream processing and AI analysis.

AI Processing & Prompt Engineering

Designed and continuously refined AI workflows responsible for transforming raw business information into meaningful application content.

Key areas of focus included:

• Prompt engineering for content generation
• Information extraction and summarization
• Structured content transformation
• Accuracy and consistency improvements
• Response quality evaluation

Special attention was given to balancing output quality with operational constraints such as response latency and API costs, ensuring the solution remained practical for real-world usage scenarios.

High-Performance Backend Architecture

Implemented backend components optimized for near real-time processing to support an interactive user experience.

Performance considerations included:

• Efficient data processing pipelines
• Low-latency service communication
• Parallelized processing workflows
• Request throughput optimization
• Resource-efficient AI integration

The resulting architecture enabled users to receive generated app previews within minutes while maintaining responsiveness across the system.

End-to-End Content Generation Pipeline

Contributed to the integration of multiple subsystems into a cohesive automated workflow.

The pipeline included:

1. Business discovery and selection
2. Data extraction from public sources
3. Content normalization and enrichment
4. AI-driven analysis and transformation
5. Delivery of generated app content to the frontend

This approach demonstrated how AI and automation can significantly reduce manual content creation efforts during software product onboarding.

Agile Development & Collaboration

Worked within a cross-functional Scrum team consisting of students from:

• Computer Science
• Business Informatics
• Design

The project was conducted under academic supervision and in collaboration with an industry partner, requiring regular sprint planning, reviews, stakeholder presentations, and interdisciplinary coordination.

This environment provided practical experience in translating technical solutions into business value while collaborating closely with designers and domain experts.

Technologies

Backend Development

• REST APIs
• Data Processing Pipelines
• Web Crawling & Parsing

Artificial Intelligence

• OpenAI APIs
• Prompt Engineering
• AI-Assisted Content Generation

Software Engineering

• Agile / Scrum
• Cross-Functional Development
• System Integration
• Performance Optimization

Key Achievements

• Developed automated pipelines for extracting and normalizing business information from public online sources
• Engineered AI workflows that transformed raw business data into application-ready content
• Optimized prompts and processing logic for response quality, latency, and operational cost efficiency
• Built backend services capable of supporting near real-time content generation
• Integrated data acquisition, AI processing, and frontend delivery into a seamless end-to-end workflow
• Collaborated successfully in an interdisciplinary Scrum team with academic and industry stakeholders
• Demonstrated how AI-driven automation can significantly accelerate business application creation