Digital Asset Intelligence Platform

Client: 

A pioneer in digital asset intelligence, delivering three core service lines:

1. Institutional Services: Provides comprehensive market insights and advanced API solutions to over 150 leading institutions, enabling sophisticated quantitative trading strategies.
2. Data Redistribution: Delivers institutional-grade datasets to major trading venues and retail platforms, ensuring reliable market intelligence across the trading ecosystem.
3. Token Services: Offers comprehensive token issuer support through investor relations dashboards, quarterly reporting, and data-driven business intelligence solutions.

Challenge: 

The client needed to build a platform that would 

• Consolidate multiple data sources into one platform 

• Replace 30+ separate tabs with a single comprehensive resource 

• Handle continuous high-frequency data updates 

• Process diverse data types 

• Maintain consistent user experience 

• Integrate distributed applications 

• Optimize performance at scale 

Solution Overview:

Core Components:

1. High-Frequency Data Management: Implemented a robust data processing infrastructure combining Rails, PostgreSQL, Redis, and Elasticsearch to handle real-time market data streams with minimal latency.
2. Data Type Processing: Developed a flexible data modeling system using PostgreSQL to accommodate diverse market data formats and ensure comprehensive information management across all asset classes.
3. User Experience Framework: Created a unified design system with reusable components and intuitive navigation based on iterative user testing to deliver a seamless platform experience.
4. Distributed Application Integration: Built a microservices architecture with API gateways to ensure reliable cross-platform data synchronization and system-wide consistency.
5. Performance Optimization: Engineered a high-performance system using code optimization, database indexing, caching, and auto-scaling serverless architecture to handle market volatility.

Result:

• Reduced complexity by consolidating 30+ separate data sources into a single unified platform  

• Engineered robust auto-scaling architecture to handle peak market volatility  

• Enhanced data accessibility through streamlined user-centric interface  

• Established new efficiency benchmarks for market data processing 

Technical Stack:

• Backend: Ruby on Rails, Python, Serverless, AnyCable, Postmark, Git 

• Frontend: Vue.js, Tailwind CSS, Vite, Inertia.js, Nuxt.js, Typesense, AG Grid

• Database: PostgreSQL, SingleStore, dbt Cloud, Elasticsearch, Redis 

• Cloud Technologies: AWS, GitHub Actions, Jenkins, Docker, Vercel 

• Monitoring Tools: AppSignal, Honeybadger, Sentry