Machine Learning Integration

Machine Learning Integration

Machine learning brings in substantial value to our clients through increasing efficiency, making better decisions, and extracting much knowledge from the data. One of the main benefits is the automation of complex tasks. Machine learning algorithms often can process vast amounts of data faster than a human and automate repetitive or time-consuming tasks thus boosting productivity and making employees focus on more high-value work, which eventually leads to increased efficiency. The other prominent benefit is predictive insight. Machine learning models can scan historical data to look for patterns and trends, which allows a business to make informed predictions. For example, ML can predict customers' future behavior, like the possibility of chance churn or purchase trend, enabling the company to act on these predictions beforehand to fix problematic issues or swing in on opportunities. Predictive ability allows businesses to optimize their strategies, hence accelerating decision-making as well as focused efforts towards enhancing customer satisfaction.

Machine learning also enhances personalization. Analyzing users' preferences in real time, the ML algorithms can tailor products, services, and marketing efforts for the optimal needs of individual customers, thereby making the customer experience more engaging; thus, making the customer stay longer and raise revenue. For example, recommendations on product offerings or content customized to a buyer on e-commerce will enhance the conversion rate by a margin.

Furthermore, it is a means through which businesses can acquire more profound insights from their data in light of better data processing and analysis. ML ensures that large datasets are no longer burdens but rather a rich source for informing innovation and better decision-making. Therefore, it is more agile in market changes, optimization of operations, and betterment of general outcomes of business.

Our customers can discover new opportunities, attain better efficiency in operation and competitiveness by combining the power of machine learning.

Recent Portfolio Projects

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Zoho Doc

Zoho Doc

This project was developed for a care and legal services provider to streamline operations through a GDPR-compliant digital system. It includes a Legal Representative Portal (EV Portal) for secure client management, an intelligent Route & Assignment Planning module to automate staff scheduling and routing, and a Billing system that applies client-specific rates and generates structured invoices. Together, these solutions replace manual processes with automation, ensuring compliance, transparency, and operational efficiency.

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Medical billing and Revenue cycle management

Medical billing and Revenue cycle management

Medical Billing is a cloud-based charge capture solution designed for doctors to streamline patient list, accelerate billing, and optimise revenue capture by retrieving patient encounter details from EHR systems and leveraging Azure services. The solution aims to revolutionise healthcare charge capture by providing a user-friendly, efficient, and accurate solution that enhance revenue capture, improve operational efficiency and reduce administrative burdens for healthcare providers and organisations. By automating rounding list, the solution aims to facilitating streamlined patient assessment and service documentation during rounds, thereby enhancing overall workflow efficiency and billing accuracy. 
Built on Microsoft Azure, system leverages Azure App Services for a scalable web application and Azure Kubernetes Service (AKS) for efficient micro services deployment. 
Azure SQL Database and Azure Blob Storage securely manage patient records, financial transactions and medical documents, while Azure Key Vault ensures encryption and compliance with security standards. 
Azure API Management (APIM) enables seamless integration with third-party services.  
To automate claim processing and real-time tracking we have leveraged Azure Logic Apps and Azure Functions streamline data synchronisation and workflow execution.   

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AI-Driven Research & Reporting for Chronic Disease Care

AI-Driven Research & Reporting for Chronic Disease Care

This project delivers an integrated AI and analytics platform for the Foundation for Sickle Cell Disease Research (FSCDR). It connects ECW (eClinicalWorks) EHR data with advanced AI-based predictive models to identify high-risk patients, automate follow-ups, and streamline state grant reporting (CMO99, CMOAE Tasks 5–13).
The goal is to transform static EHR data into actionable insights — improving research visibility, compliance, and patient outcomes while cutting down manual reporting workloads. The solution supports predictive ER-risk modeling, AI-based outreach automation, and Power BI-driven compliance dashboards across FSCDR’s Centers of Excellence.

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What our clients say about smartData

Christopher

Christopher

It’s been a great experience working with smartData. I am...

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smartData Benefits

Global Talent Pool

We boast nearly 1,000 highly skilled developers strategically positioned across three offshore locations, enabling us to deliver world-class software solutions. 

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smartData Enterprises boasts a robust global footprint, with a strong foothold in key regions such as the US, Australia, Europe, and Japan.

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