To deliver its solutions, SmartQR needed a cloud provider that offers the compute capabilities and scalability to process large medical diagnostics datasets and train AI models on them. Operating in the highly regulated healthcare space, SmartQR also needed to ensure its management of patient data would comply with the European Union’s General Data Protection Regulation and the Health Insurance Portability and Accountability Act (HIPAA) in the United States. This required robust identity-based access control, audit logs, and encryption.

“Managing these large volumes of sensitive and diverse data, including medical images, patient records, and diagnostic reports, in accordance with strict compliance requirements, was essential to our business,” says Sambit Ghosh, Founder and Group CEO.

“We also needed to integrate seamlessly with healthcare institutions, research providers, and our other technology partners so we could securely share data with them. This led us to Google Cloud.”

The Google Cloud team briefed SmartQR on relevant AI and machine learning products and high-end GPUs designed to handle the large workloads and datasets needed for its AI-powered solutions. This would accelerate model training and enhance the accuracy and efficiency of diagnoses using SmartQR products. Together, the teams determined that Google Cloud would support SmartQR’s needs, enabling the business to develop and test its AI algorithm, remain within budget, and meet requirements for performance, reliability, and compliance.

The organization now relies on a range of Google Cloud services to provide the scalability and reliability to achieve its business objectives, delivered with usage-based billing to manage budgets. Cloud Run and Cloud Functions streamline development and minimize the need for its developers to manage infrastructure, while Vertex AI enables them to generate the AI and machine learning outputs that run in SmartQR’s products. BigQuery provides a robust, scalable data warehouse, with Pub/Sub providing the associated data pipelines. The organization is currently experimenting with BigQuery ML for data analytics queries.

Google Cloud also provides the scalability SmartQR needs to manage demand spikes, which can lead to more than a million users using its AI-powered applications at one time. “Over the past three months, we have seen a tremendous response from the market, and the scalability of Google Cloud has enabled us to handle increased user traffic and growing datasets without compromising performance and availability,” says Ghosh.   

Meanwhile, automation through Cloud Scheduler and other Google Cloud services has enabled SmartQR to streamline its operational workflows, including data processing and model training and deployment. “Thanks to Google Cloud, we can be very frugal with our technical resources, and enhance operational efficiency by at least 30% compared to our previous environment,” explained Ghosh.

The benefits of SmartQR’s use of Google Cloud flow through to the end users of the company’s medical diagnostic products. “Traditionally, even if you needed a very basic diagnostic test, you needed to call a service provider who would come to your home, collect blood, and send you the results in up to 12 hours,” says Ghosh. “This type of service was not really accessible to many people in India for reasons such as cost.”

With SmartQR’s advanced AI services, a person just needs an internet-connected device to diagnose their basic physical parameters in as little as two minutes from the comfort of home or at a pharmacy, at a very low cost. If there is a problem outside those parameters, they can then seek secondary or tertiary care.