Technical Solutions

Case studies of engineering solutions that solved complex business problems.

CO

Construction Document Management Platform

Digitized paper-based workflows for a construction firm, reducing document processing time by 72%.

Business Impact

Reduced document processing time from 4 days to 1 day. Improved accuracy by 34%. Saved $150K annually in administrative costs. Enabled real-time project tracking across 27 construction sites.

Technical Solution

Implemented a microservice architecture with TypeScript backend services, React frontend, and Prisma ORM for database access. Built custom OCR pipeline using Tesseract.js with pre/post-processing for construction document digitization.

TypeScriptNode.jsReactPrismaPostgreSQLTesseract.jsDocker
RE

Real-time Financial Data Pipeline

Engineered high-throughput data processing system handling 3,500 transactions/second for a financial services company.

Business Impact

Reduced data processing latency from 2.5 minutes to 200ms. Enabled real-time fraud detection, preventing an estimated $2.1M in fraudulent transactions annually. Scaled to handle 3x the transaction volume without infrastructure changes.

Technical Solution

Created a FastAPI backend with async processing capabilities, Pydantic for data validation, and SQLAlchemy ORM. Implemented Kafka for event streaming, Redis for caching, and custom partitioning for horizontal scaling.

PythonFastAPIKafkaRedisPostgreSQLDockerAWS
AU

Automated Trading Platform

Developed low-latency trading system with algorithmically optimized execution strategies.

Business Impact

Achieved 18% improvement in trade execution prices. Reduced execution latency by 65ms. Automated portfolio rebalancing saved 22 hours of manual work weekly. Generated 34% higher returns compared to manual trading.

Technical Solution

Built with Node.js and TypeScript for transaction handling and blockchain SDK integration. Implemented custom trading strategies with backtesting capabilities, automated execution, and real-time market data processing.

TypeScriptNode.jsWeb3.jsRedisWebSocketsAWS Lambda
AI

AI-Powered Sales Engine

Built recommendation system that increased user engagement by 47% for a digital content platform.

Business Impact

Increased average session duration by 2.7 minutes. Improved content discovery by 62%. Boosted conversion rate by 23%. Reduced content production costs by $85K annually through better targeting.

Technical Solution

Developed using Next.js with server components, TypeScript for end-to-end type safety, and edge functions for AI response streaming. Implemented vector embeddings for content similarity and personalization.

TypeScriptNext.jsReactOpenAI APIPostgreSQLVector DatabaseWebSockets