Enhanced User Experience and Targeted Marketing through Customer Data Platform

A company faced challenges in effectively targeting its diverse user base and understanding individual customer preferences and travel patterns. This limited the success of their marketing campaigns, especially in-app advertising, and hindered personalized user experiences.

Enhancing Document Data Extraction with AI-Powered Automation

Managing thousands of contract documents manually is time-consuming and inefficient. To overcome this, an AI-driven solution was implemented, combining Vision AI for document scanning and Gemini AI for extracting employee profile data. A comprehensive layout management system ensured precise document organization, improving efficiency and accuracy.

Optimizing Data Performance with Cloud Migration

To overcome ETL slowness and sluggish dashboard performance, a cloud-based transformation was implemented. By migrating from PostgreSQL to BigQuery (BQ) and relocating the Tableau server to Google Cloud Platform (GCP), the solution significantly enhanced data processing speed and dashboard rendering.

Enhancing Customer Engagement with AI-Powered Search & Messaging

To overcome ETL slowness and sluggish dashboard performance, a cloud-based transformation was implemented. By migrating from PostgreSQL to BigQuery (BQ) and relocating the Tableau server to Google Cloud Platform (GCP), the solution significantly enhanced data processing speed and dashboard rendering.

AI-Driven Stock Visibility & Availability Management

Limited stock visibility, inefficient manual tracking, and lack of AI-driven insights often lead to delays and missed opportunities. To address this, an AI-powered solution was developed using Google Cloud Platform, leveraging Object Detection AI for real-time tracking and Looker for dashboard-driven insights and availability monitoring integrating technologies like AutoML Vision, Vision API, Looker, BigQuery, AI Platform, TensorFlow, and AppSheet.

AI-Driven Customer Profiling for Enhanced Marketing

Manually input customer data often lacks validation and accuracy, leading to ineffective targeting in marketing efforts. To address this, an AI-powered classification model was developed to predict gender, income group, and age with high precision. Using data exploration, feature extraction, and machine learning, the model was built and deployed in BigQuery for seamless integration.

AI-Powered Automation for Safety & Operational Efficiency

Manual component inspections, fatigue detection, and excavator activity monitoring lacked accuracy and standardization, leading to human errors and safety risks. To enhance efficiency and safety, an AI-powered solution was implemented using Machine Learning with TensorFlow, Python, and Kubernetes.

AI-Powered Fraud Detection & Cost Optimization

Detecting fraudulent transactions in real-time was a challenge, leading to potential financial risks and inefficiencies. To address this, an AI-driven fraud detection system was developed using Google Cloud technologies. We built 7 types of fraud detection models, including Promo Abuse, Account Takeover, and Money Laundering. This project combined various Google Cloud products like BigQuery, BigQuery ML, and AI Platform to enhance analytics, monitoring, and reporting.

Optimizing IT Infrastructure with Cloud-Native Transformation

Managing on-premise servers and VPS created operational inefficiencies and hindered experimentation and scalability. To address this, a cloud-native transformation was implemented, equipping the team with modern infrastructure and technical expertise for seamless adoption.

Empowering Digital Banking with Cloud Technology

Expanding financial access and making data-driven lending decisions required a secure, scalable, and user-friendly digital banking solution. To achieve this, a cloud-native mobile banking app was developed, integrating digital KYC, financial tools, and seamless e-commerce payments.

Our Experience