medical_records_processing · healthcare · workflow
SmartQR uses Google Cloud and Vertex AI to deliver AI-powered health diagnostics in India
SmartQR needed a cloud provider capable of handling large medical datasets, training AI models efficiently, and ensuring patient data privacy while scaling to more users and markets.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Medical data storage and pipeline
BigQuery and Pub/Sub handle data storage and pipelines.
Tools used
Google CloudCloud RunCloud FunctionsVertex AIBigQueryPub/SubGoogle Kubernetes EngineCompute EngineCloud StorageSecurity Command CenterTensorFlow
Outcome
SmartQR boosted efficiency by 30%, improved diagnosis accuracy, cut costs, and expanded healthcare access for millions in India.
Results
Volume30%
Cost replacedcut costs
Grounding & classification
Source type: platform led case
26 fields verified against source quotes.
predictive analyticsmedical recordmetric backednamed customertools describedworkflow describedhealthcareaccuracy improvementcost reductionemployee productivityplatform led casemedical records processing