Overview

To establish a scalable, secure, and automated Google Cloud foundation for multiple operating companies (Opcos) using Terraform, ensuring efficient infrastructure provisioning, compliance, and governance.

Overview

To deploy a scalable, AI-powered WordPress infrastructure using Google Kubernetes Engine (GKE), Vertex AI, and BigQuery ML to support high-volume advertising funnels with real-time traffic optimization, predictive analytics, and enhanced security.

Overview

A global leader in environmentally safe fire suppression systems, this company designs, develops, and manufactures its own fire safety products for high-risk industries such as mining, energy, and industrial operations. To enhance fire suppression system reliability and efficiency, the company deployed an IoT-enabled real-time monitoring system integrated with Google GenAI, Vertex AI, and machine learning-based predictive maintenance.

Overview

Develop a Vue.js-based admin panel for managing Google Workspace users, directory permissions, and document templates, providing a streamlined alternative to the Google Admin Console.

Overview

In the field of platform engineering, the objective was to streamline infrastructure deployment and resource provisioning while optimizing costs, enhancing security, and reducing operational overhead. The project focused on Google Cloud Platform (GCP), integrating tools like Backstage, GitHub Actions, and Terraform to create a developer-friendly, automated workflow that ensured efficient, secure, and scalable cloud operations.

Overview

A leading medical services company faced critical compliance challenges related to its digital advertising and website content. The medical industry operates under strict regulatory frameworks, and non-compliant keywords in advertisements or website content could lead to: Regulatory fines and penalties Ad disapprovals and account suspensions Reputational damage The client needed a scalable, automated solution that could monitor multiple advertising platforms—including Google Ads, Bing, and Facebook Ads—to detect and flag non-compliant terms in real time.

Overview

To enhance user engagement and drive conversions, the company developed a real-time data pipeline that processes 4 million user activity events per hour and delivers personalized product recommendations within 5 seconds. By leveraging Google Cloud Dataflow, Apache Beam, Pub/Sub, and Bigtable, the system efficiently categorizes user actions, applies business logic, and provides dynamic recommendations, ensuring a seamless shopping experience.

Overview

A leading Medical Services company required a highly scalable and automated lead flow orchestration system to manage complex real-time lead qualification across multiple CRM systems. Their existing manual process caused: Delays in lead qualification Inconsistencies in data across CRMs Lost revenue opportunities due to inefficiencies To solve these challenges, we built a Google Cloud-powered lead orchestration solution that automated lead validation, improved synchronization across CRMs, and provided real-time, scalable lead management.

Overview

A well-known U.S. talent agency needed an intelligent chatbot to automate and streamline interactions between job-seeking talent and hiring employers. The existing live chat system required 25 human agents to manually handle thousands of daily queries, leading to high operational costs, delays, and inconsistent user experiences reduced to 5 human agents. Key challenges included: High Human Workload – Too many queries required manual responses, reducing efficiency. Context-Switching Complexity – Talent and employer queries required different knowledge bases, making a single bot ineffective. Delayed Resolution – Escalations to human agents caused long wait times. Lack of Real-Time Monitoring – No way for human agents to oversee conversations in real time. Scalability – The system was unable to handle surges in demand without hiring additional staff.

Overview

This project focuses on automating and improving the service review process in the industry by leveraging Google Dialogflow for AI-powered conversational interactions. Customers can provide feedback via email and live chat while also engaging with a live representative when needed. The system ensures seamless communication, captures qualitative feedback, and schedules follow-ups using Google Calendar integration.

Overview

The project aimed to automate and streamline the process of notifying policyholders about their upcoming insurance coverage expiration and facilitating seamless renewal options. By leveraging Google Dialogflow, Google Cloud Functions, and Google Calendar API, the system enables timely reminders and intelligent chatbot interactions to assist customers in renewing their policies efficiently.

Overview

A 200-person service team working in legal consultations required a seamless and efficient way to retrieve answers from a centralized knowledgebase. The company needed a real-time AI-powered assistant integrated into Slack, allowing employees to quickly get relevant answers to legal and procedural queries. The solution leveraged Google Dialogflow, Google Cloud Run, and Node.js to provide an interactive Slack bot that responds instantly to employees' questions by querying a pre-built knowledgebase. Additionally, the bot integrated with the Google Calendar API to assist with scheduling consultations and meetings.

Objective

The Slack Message Aggregation System was developed to collect and centralize conversations from hundreds of channels across multiple Slack workspaces. By leveraging Dialogflow, Google Cloud Functions, and Google Sheets, the system aggregates messages where the bot is present and transmits them to designated centralized channels within a corporate Slack workspace. This project was designed to improve visibility, compliance, and communication retention for teams supporting a large financial client. Developed in collaboration with one of the largest security software companies in the world, the system was implemented for a top five financial institutions in the United States to streamline cross-workspace messaging and compliance tracking.

Objective

To develop a real-time fleet management UI powered by Enterprise Google Maps and Contact Center AI (CCAI), enabling a large fleet management company to monitor thousands of vehicles, track real-time locations, optimize last-mile deliveries, manage maintenance schedules, and provide AI-powered customer support.

Objective

To automate the extraction, normalization, and reporting of over 100,000 financial records using Google Gemini AI and Document AI (DocAI). This project transformed raw CDATA-formatted financial data into structured, analyzable formats while integrating a Python-based connector service to update the customer’s CRM with processed insights.