Case Studies
Deep dives into real projects showing the challenges faced, solutions implemented, and measurable business outcomes achieved.
ClassCharts EdTech Platform
Scaling from startup to millions of users
The Challenge
Joined ClassCharts as the first developer hire after the CTO when the platform was serving thousands of UK schools. The challenge was to scale the system to handle millions of users while maintaining reliability and adding new features for teachers, students, and parents.
Key Technical Challenges
- Database performance bottlenecks with growing user base
- Real-time notifications for millions of users
- Complex permission system for schools, teachers, students, and parents
- Mobile app synchronization and offline capabilities
- GDPR compliance and data protection
Solutions Implemented
Database Optimization
- Implemented strategic indexing reducing query times by 80%
- Added read replicas for reporting and analytics
- Optimized complex joins and introduced materialized views
Scalable Architecture
- Migrated from single server to cloud infrastructure
- Implemented load balancing and auto-scaling
- Added Redis caching layer reducing load by 60%
Real-time Features
- Built WebSocket system for instant notifications
- Implemented message queuing for reliable delivery
- Added push notifications for mobile apps
Quality Assurance
- Introduced comprehensive test suite (unit, integration, E2E)
- Set up CI/CD pipeline reducing deployment time by 90%
- Implemented monitoring and alerting systems
Business Impact
Performance Improvements
- Page load times reduced from 5s to under 1s
- System downtime reduced from hours to minutes per month
- Database query performance improved by 80%
- Mobile app crash rate reduced to under 0.1%
Business Growth
- Platform scaled to serve millions of users
- Enabled expansion to international markets
- Supported 10x increase in concurrent users
- Reduced infrastructure costs per user by 40%
Technologies Used
Government IoT Smart City Platform
Nationwide infrastructure for connected devices
Project Overview
Designed and implemented the backend architecture for a Middle Eastern government's nationwide smart city initiative. The system needed to securely process and analyze data from thousands of connected devices across multiple urban areas while meeting strict government compliance requirements.
Architecture Highlights
- Microservices architecture with Kubernetes orchestration
- Event-driven design using Apache Kafka
- Time-series data storage with Cassandra
- Real-time analytics and alerting system
- Multi-region deployment for high availability
Security & Compliance
- End-to-end encryption for all data transmission
- Role-based access control with audit logging
- Government-grade security protocols
- GDPR and local privacy law compliance
- Penetration testing and security audits
Technical Stack
Philips Healthcare & Lighting
High-Compliance Frontend Architecture for Enterprise
The Challenge
Lead frontend architecture for Philips' digital innovation projects, specifically focusing on complex B2B configurator tools. The requirement was to build pixel-perfect, high-performance applications that integrated seamlessly with legacy enterprise systems while adhering to strict regulatory and brand compliance standards.
Solutions Implemented
Enterprise Configuration Engine
- Developed a dynamic rules engine for complex product configurations
- Ensured real-time validation of thousands of component combinations
- Integrated with SAP/ERP systems for real-time pricing and stock
Compliance & Security
- Implemented strict data handling protocols compliant with GDPR
- Ensured accessibility compliance (WCAG 2.1) for global markets
- Built secure authentication flows integrating with corporate SSO
Technologies Used
RWE & Innogy Energy Systems
Real-Time Data Visualization for Renewable Energy
The Challenge
Developed critical energy management applications for RWE and its renewable subsidiary, Innogy. The goal was to visualize complex telemetry data from renewable energy assets in real-time, providing actionable insights for energy management and grid stability.
Solutions Implemented
Data Visualization
- Built interactive dashboards using D3.js and Canvas
- Visualized kilowatt-hours, peak loads, and generation mix
- Optimized rendering performance for high-frequency data streams
System Reliability
- Architected fault-tolerant frontend systems for critical uptime
- Implemented offline-first capabilities for field engineers
- Ensured secure data transmission for critical infrastructure
Technologies Used
MarketAlerts
AI-powered market intelligence and trade ideas
The Challenge
Build a comprehensive AI-powered financial platform that monitors global markets 24/7 and provides intelligent alerts for various market events. The system needed to process real-time market data, analyze patterns using AI, and deliver personalized notifications to traders and investors across 20+ international markets.
AI-Powered Features
- Earnings call and report summarization
- Technical chart pattern recognition
- Insider transaction monitoring
- Analyst rating change detection
- M&A and product announcement tracking
- Financial guidance change alerts
Technical Architecture
- Real-time data ingestion from multiple sources
- AI-powered content analysis and classification
- Scalable notification system
- Multi-market data normalization
- Advanced watchlist management
- Mobile-responsive dashboard
Key Achievements
Platform Capabilities
- 24/7 monitoring of global financial markets
- AI-driven pattern recognition and alerts
- Support for 20+ international stock exchanges
- Real-time price and volume analysis
- Intelligent notification prioritization
User Experience
- Intuitive watchlist creation and management
- Customizable alert preferences
- Mobile-optimized interface
- Interactive market data visualization
- Product Hunt featured launch
Technology Stack
Metis: AI Market Intelligence
Real-time News Aggregation & Trading Signals Platform
The Evolution
Originally born as a spin-off from Plutus (a personal trading platform), Metis evolved into a standalone beast. The goal was simple but ambitious: ingest news from thousands of sources in real-time, understand it using AI, and correlate it with market data to find trading signals before the market reacts.
Advanced Data Pipeline
- Ingestion: 5000+ RSS feeds, newsletters, and archives monitored 24/7
- Storage: Polyglot persistence using PostgreSQL (relational), ClickHouse (analytics), and Meilisearch (search)
- Queueing: Robust event-driven architecture powered by RabbitMQ and BullMQ
AI & Intelligence
- Classification: Auto-tagging topics and detecting relations between entities
- Summarization: LLM-powered summaries (OpenAI, Anthropic, Ollama)
- Market Data: Integration with Alpaca and Binance for real-time price feeds
The Tech Stack
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