Trehan Data features projects across industries in different niches on all major cloud platforms
In a clinical trial environment, a healthcare organization sought to automate symptom monitoring using video and audio feeds from patient rooms. The goal was to reduce staff workload while improving patient comfort and response times. By integrating Google Cloud services with TensorFlow Lite, w ebuilt a real-time, edge-deployable machine learning system for audio/visual symptom assessment—laying the groundwork for scalable, intelligent healthcare automation.
AI tools enabled real-time monitoring of patient vital signs and symptoms for early intervention and treatment optimization.
An e-commerce platform serving both people and pets implemented an AI-driven recommendation engine to personalize the shopping experience and increase conversion rates. Leveraging AWS infrastructure and Python-based machine learning models, the system intelligently recommended products using a blend of user behavior, product attributes, and contextual metadata—resulting in measurable gains in both conversion and average order value (AOV).
Ecommerce workflows in GCP delivered individualized product recommendations and promotions driving higher conversion rates.
A consulting firm needed a faster, scalable way to analyze dozens of hours of recorded interviews across multiple projects. Manual transcription and data extraction were time-consuming and inconsistent, often delaying client deliverables. By implementing an automated Microsoft Azure-based workflow, the firm reduced research time by 66%, built a searchable archive of insights, and unlocked new service offerings.
The team implemented a modular, automated pipeline using Microsoft Azure’s speech and language services, enabling end-to-end processing of interviews—from raw video to dashboards of insights.
Each analysis step is modular—allowing the team to offer different service tiers:
The system is adaptable across domains: legal, customer support, academic research, and more.
A travel security client needed to monitor global OSINT like social media chatter to detect emerging threats, unrest, and public sentiment. Manual analysis across multiple languages and platforms was inefficient and reactive. By leveraging Google Cloud’s language and translation APIs, they built an automated multilingual analysis system that enabled real-time insights, reduced analyst workload, and uncovered location-specific risks proactively.
The team designed a cloud-native pipeline on Google Cloud that automated the ingestion, translation, analysis, and visualization of global social media data.
The system also lays the groundwork for automated content creation—future iterations include feedback loops for content generation and publication based on trending topics.
An insurance provider needed to modernize its claims processing pipeline, which was hindered by manual data entry, inconsistent document formats, and a growing backlog. By combining Robotic Process Automation (RPA) with Google Cloud's AI suite, the company reduced claim cycle times by 40% and lowered processing errors by 25%, while enhancing fraud detection and customer satisfaction.
The solution can easily generate 100+ distinct workflows annually. Specialized claim types, Custom risk thresholds per product line, Localization for different compliance requirements, Integration with ERP, legal, and case management systems.
With 5 years of experience applying the latest cloud, analytics and automation technologies across industries, Trehan Data has the expertise to automate processes, analyze data and build intelligent solutions tailored to each client's specific needs and goals.