A high-throughput, low-latency inference pipeline processing 50K+ predictions/sec for forex trading signals. Built with a microservices architecture featuring real-time feature engineering, A/B model serving via MLflow, and Redis-backed caching for sub-10ms response times. Deployed on Kubernetes with auto-scaling based on market volatility indices.

An autonomous multi-agent system that researches trending topics, writes scripts, generates voiceovers, and assembles YouTube Shorts with zero human intervention. Orchestrated via CrewAI with specialized agents for research, copywriting, and video assembly. Processes 100+ videos/day with a 3-agent pipeline achieving 92% topic relevance scores.

A context-aware productivity assistant that uses Retrieval-Augmented Generation to provide personalized focus strategies. Integrates LlamaIndex for document indexing, Pinecone for vector search, and a Next.js frontend with real-time WebSocket updates. Achieved 40% improvement in user focus session completion rates through adaptive break scheduling.