Building AI Systems That Scale

The Challenge

Insurance shopping is complex with 100K+ permutations affecting quotes. Customers spend weeks comparing providers across zip codes, coverage levels, and deductibles, yet still feel uncertain. Policy terms are confusing, prices vary wildly by location, and people constantly change their minds (moving cities, adjusting coverage). Traditional comparison tools can't handle this complexity at scale.

The Solution

Built interactive AI demos showing how machine learning analyzes every factor—location, age, driving history, policy design—to generate instant, personalized recommendations. Developed comprehensive synthetic dataset mimicking real insurance pricing algorithms. Created workflow simulator where users adjust age, location, and coverage to see real-time price changes and test "what-if" scenarios. AI chat assistant answers insurance questions using natural language parsing.

Key Metrics

Results & Impact

• Interactive workflow: adjust age/location/coverage with instant feedback
• Real-time what-if scenarios show price changes as users explore options
• Synthetic dataset with 500,000+ possible permutations
• AI chat answers complex insurance questions (coverage, savings, accidents)
• Shows how moving cities impacts premiums across 12 anonymized insurers
• Translates policy fine print into plain English summaries

The Challenge

Enterprise healthcare platform stuck in 3-week synchronized release cycles. Four portal teams (Patient, Provider, Admin, Billing) can't deploy independently. One team's bug blocks everyone. Coordination meetings consume hours. Merge conflicts daily. Team frustration high. Innovation velocity: 17 releases per year.

The Solution

Transform monolithic platform into microfrontend architecture using Webpack Module Federation. Each portal becomes independently deployable application with own repo, CI/CD pipeline, and deployment schedule. Teams own complete user experience—from UI through API integration—while seamlessly consuming shared Auth, Data, Payment, and Notification services via standardized contracts. Feature flags enable dark launches and A/B testing per portal without coordination.

Key Metrics

Results & Impact

• Deployment frequency: 3 weeks → Daily (21× faster feature delivery)
• 100% team autonomy - each team deploys independently
• Coordination meetings: 4 hours/release → 0 hours
• Blast radius reduced 75%: Bug in one portal doesn't affect others
• Feature velocity: 17/year → 260/year (per portal)
• Developer satisfaction up 80% - teams can innovate freely

The Challenge

Creating music using AI from user-provided melodies and distributing it at massive scale presented unprecedented challenges. The platform needed to generate unique AI-powered music tracks from user input, process millions of concurrent creation requests, manage content rights for AI-generated music, and deliver 600M+ streams with sub-second latency.

The Solution

Architected an end-to-end AI music creation and streaming infrastructure using AWS (Lambda, CloudFront, S3) with deep learning models for music generation. Built scalable pipeline to process user melodies through AI models, generate unique tracks, and instantly distribute globally. Developed patented multi-track content management system enabling selective track inclusion based on user permissions. Integrated deep learning for content analysis, personalization, and real-time music synthesis.

Key Metrics

Results & Impact

• Powered 600M+ streams globally
• AI music generation at scale from user melodies
• Real-time processing of millions of creation requests
• Reduced streaming latency to <500ms worldwide

The Challenge

Creators needed seamless integration between live streaming and on-demand content while maintaining Twitch-scale latency and removing copyrighted music in real-time. System had to handle 70K RPS while processing live streams, managing content rights, and archiving for on-demand viewing—all without manual intervention.

The Solution

Invented and patented two breakthrough systems (US11457245B1 & US11870830): embedded streaming content management that automatically archives live streams for on-demand viewing, and multi-track selective content delivery. Built massively scalable infrastructure using AWS Kinesis for real-time stream processing, Redshift Spectrum for analytics, Lambda for serverless compute, S3 for storage, and CloudFront for global distribution. Integrated ML/AI models for real-time music detection and removal, content categorization, viewer behavior prediction, and automated quality optimization. Maintained sub-second latency at Twitch scale while processing 70K+ requests per second.

Key Metrics

Results & Impact

• Patents: US11457245B1 (2022) & US11870830 (2024)
• Handled 70K+ RPS at Twitch-scale latency
• Real-time music removal from live streams
• Seamless live-to-VOD conversion with AI optimization
• Zero manual intervention required
• Adopted by major streaming platforms

The Challenge

An esports startup (Rimble) needed to build tournament infrastructure, real-time match streaming, and player engagement features from scratch with limited resources.

The Solution

Provided technical architecture guidance, helped select scalable tech stack, and advised on product strategy. Designed system to handle concurrent tournaments with real-time updates and integrated streaming. Implemented image recognition and ML models for automated match analysis, player performance tracking, and content moderation.

Results & Impact

• Launched MVP in 4 months
• Handled 10K+ concurrent users
• Successful seed funding round
• Featured in gaming industry publications

The Challenge

Multiple startups across fashion, travel, healthcare, dating, gig economy, and SAAS needed technical and strategic guidance to scale their products and make critical technology decisions.

The Solution

Provided architecture reviews, tech stack decisions, scaling strategies, and product roadmap guidance. Helped teams make critical build-vs-buy decisions, optimize infrastructure costs, and prepare for growth.

Results & Impact

• 10+ startups advised across industries
• Collective fundraising: $20M+
• Multiple successful product launches
• Reduced infrastructure costs by 40%+ average