Case Studies
Real-world results from our enterprise data and AI implementations.
Enterprise RAG System for Financial Services
Challenge
A leading financial institution needed to make decades of proprietary research and compliance documents searchable and accessible to analysts while maintaining strict data security and regulatory compliance.
Solution
Implemented a production-grade RAG system using Pinecone vector database integrated with their private LLM infrastructure. Built custom document processing pipelines using dbt and Airflow to chunk, embed, and index 500,000+ documents.
Results
- ✓85% reduction in research time for analysts
- ✓99.9% system uptime with enterprise-grade reliability
- ✓Full compliance with financial regulations (SOC 2, GDPR)
- ✓Processing 10,000+ queries daily with sub-second response times
Technologies Used
Business Impact
$2M annual savings in analyst productivity
Modern Data Stack Migration for Gaming Company
Challenge
A gaming company with 100M+ active users struggled with legacy data infrastructure that couldn't scale. Their analytics team spent 70% of time on data quality issues rather than insights.
Solution
Architected and implemented a complete modern data stack migration from on-premise databases to Snowflake. Built 50+ dbt models for data transformation, integrated Airbyte for real-time data ingestion, and deployed Airflow for orchestration.
Results
- ✓100GB+ daily data processing with 99.9% reliability
- ✓60% reduction in data quality issues
- ✓10x faster analytics query performance
- ✓Enabled self-service analytics for 50+ stakeholders
Technologies Used
Business Impact
3x increase in data team productivity
Real-Time Analytics Platform for E-Commerce
Challenge
An e-commerce platform needed real-time visibility into customer behavior, inventory, and sales performance across 1,000+ stores to optimize pricing and inventory decisions.
Solution
Designed streaming data architecture using Databricks and BigQuery. Built real-time dashboards in Tableau that integrate data from 15+ source systems. Implemented machine learning models for demand forecasting.
Results
- ✓Real-time dashboards updating every 30 seconds
- ✓25% improvement in inventory optimization
- ✓15% increase in revenue through dynamic pricing
- ✓Executive visibility across all business metrics
Technologies Used
Business Impact
$5M additional annual revenue
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