Our Portfolio

AI-Powered Customer Segmentation

Client: E-commerce Retail Leader

Challenge

Client had millions of customers but lacked meaningful segmentation for personalized marketing. Traditional rule-based segments were ineffective.

Solution

Implemented advanced clustering algorithms (K-means, DBSCAN) using customer behavioral data, RFM analysis, and purchase history.

Results

• 35% increase in marketing ROI
• 22% improvement in conversion rates
• Identified 12 high-value customer segments

Tech Stack: Python, TensorFlow, BigQuery, Cloud Dataflow

Real-time Data Pipeline

Client: Financial Services Company

Challenge

Processing millions of daily transactions with batch-only systems causing 24-hour delays in reporting and compliance issues.

Solution

Built scalable real-time infrastructure using Apache Kafka for ingestion and Apache Spark for processing, deployed on AWS.

Results

• 10M+ events processed daily
• 99.9% uptime achieved
• Reduced reporting latency from 24h to 5 minutes

Tech Stack: Kafka, Spark, Hadoop, AWS, Python

Healthcare Analytics Platform

Client: Multi-Hospital Healthcare Network

Challenge

Fragmented patient data across multiple systems with no unified analytics. Poor visibility into operational efficiency and patient outcomes.

Solution

Created centralized data warehouse integrating EHR, billing, and operational systems. Built interactive dashboards for real-time insights.

Results

• 10% improvement in operational efficiency
• 15% reduction in readmission rates
• Enhanced patient care quality metrics

Tech Stack: SQL Server, Power BI, Azure, Python

Predictive Maintenance System

Client: Manufacturing Leader

Challenge

Unexpected equipment failures causing downtime and production losses.

Solution

Implemented IoT sensors and machine learning models to predict equipment failures before they occur.

Results

• 40% reduction in downtime
• $2M annual savings
• 95% prediction accuracy

Tech Stack: Python, TensorFlow, IoT, Azure

Recommendation Engine

Client: E-commerce Platform

Challenge

Low engagement and conversion rates with generic product displays.

Solution

Built sophisticated recommendation engine using collaborative filtering and content-based algorithms.

Results

• 28% increase in average order value
• 45% improvement in click-through rates
• Enhanced user experience

Tech Stack: Python, Collaborative Filtering, AWS, Redis

Fraud Detection System

Client: FinTech Company

Challenge

High fraud losses and false positives impacting customer experience.

Solution

Developed real-time fraud detection using anomaly detection and supervised learning models.

Results

• 60% reduction in fraud losses
• 75% fewer false positives
• Real-time transaction scoring

Tech Stack: Python, Anomaly Detection, Kafka, GCP