Noida, 201309,
India
MothersonSumi INfotech & Designs Limited (MIND)
MothersonSumi INfotech & Designs Limited (MIND), a prominent reseller, system integrator, and consulting company, that plays a vital role in numerous system integration and digital transformation initiatives. MothersonSumi INfotech & Designs Limited (MIND) collaboration with software players such as Amazon Web Services (AWS) empowers organizations to embrace disruptive technologies and accelerate their journey to the cloud, thus reshaping their business models.
| Reseller and SI | Vendor | Application | Category | Market |
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| MothersonSumi INfotech & Designs Limited (MIND) | Amazon Web Services (AWS) | Amazon CloudWatch RUM | Application Performance Management | ITSM |
| MothersonSumi INfotech & Designs Limited (MIND) | Amazon Web Services (AWS) | Amazon DynamoDB | Database Management | IaaS |
| MothersonSumi INfotech & Designs Limited (MIND) | Amazon Web Services (AWS) | Amazon Lambda | Apps Development | PaaS |
| MothersonSumi INfotech & Designs Limited (MIND) | Amazon Web Services (AWS) | Amazon S3 | Cloud Storage | IaaS |
| MothersonSumi INfotech & Designs Limited (MIND) | Amazon Web Services (AWS) | Amazon Textract | Intelligent Document Processing | Content Management |
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Product | Category | When | Insight |
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Max Healthcare Institute | Healthcare | 15000 | $548M | India | Amazon Web Services (AWS) | Amazon CloudWatch RUM | Application Performance Management | 2021 |
In 2021 Max Healthcare Institute implemented Amazon CloudWatch RUM as part of its Application Performance Management approach to gain runtime visibility into an AWS serverless document processing pipeline. The deployment aligned with an automation initiative focused on supplier document ingestion and accounts payable operations that previously required a 29 person back-office and accounts payable workforce across Max Healthcare facilities and affiliated services such as Max@Home and Max Labs.
Amazon CloudWatch RUM was instrumented alongside a serverless OCR solution built and delivered by MothersonSumi Infotech & Designs Limited, MIND, which leveraged Amazon Textract for extraction. Amazon CloudWatch RUM was used to capture real user monitoring signals and frontend performance telemetry, while the document processing stack implemented standard Application Performance Management capabilities including traceability of invocation flows, error capture, and latency observation tied to backend functions. The case restates Amazon CloudWatch RUM as the monitoring plane used to observe end user and orchestration behavior for the document workflow.
The implementation integrated Amazon CloudWatch RUM with AWS services already deployed for the OCR pipeline, specifically AWS Lambda, AWS Step Functions, Amazon API Gateway, Amazon S3, Amazon DynamoDB, Amazon Textract, and Amazon A2I. Operational coverage targeted supplier document ingestion, pre processing, extraction and validation steps, and the downstream entry of processed data into DynamoDB for ERP extraction. The deployment scope encompassed accounts payable and back-office processing across Max Healthcare s 16 facilities in India and the related centralized document intake processes.
Governance and orchestration followed a scheduler driven ingestion, S3 event triggers and Step Functions orchestration, with image pre processing, Textract extraction producing form and raw outputs, post processing validation, augmented human review via A2I, and persistence into DynamoDB. MIND s solution delivered the required level of accuracy with minimal operational overhead and faster time to production, and Amazon CloudWatch RUM provided continuous application performance monitoring to support incident triage and ongoing operational governance.
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Max Healthcare Institute | Healthcare | 15000 | $548M | India | Amazon Web Services (AWS) | Amazon Lambda | Apps Development | 2021 |
In 2021, Max Healthcare Institute implemented Amazon Lambda as the compute backbone of an Apps Development solution to automate supplier document OCR and downstream data flows for back-office accounts payable. The program targeted a high-volume intake environment where a 29-person team previously processed thousands of scanned supplier documents monthly across Max Healthcare’s 16 facilities in NCR Delhi, Haryana, Punjab, Uttarakhand, and Maharashtra. The initiative is scoped to supplier invoice and document handling that feeds on-time supplier payments and downstream ERP processing.
The deployment is architected as a serverless pipeline centered on AWS Lambda functions orchestrated by AWS Step Functions, with Amazon S3 used for ingestion and Amazon Textract used for document extraction. Pre-processing image cleaning routines are executed before Textract runs, both form and raw extraction outputs are captured, and post-processing logic validates and normalizes extracted fields. Amazon Lambda hosts the processing logic and triggers, Amazon API Gateway exposes any programmatic endpoints, and Amazon CloudWatch provides observability and operational logging.
Human review is integrated through Amazon A2I to surface low confidence extractions into an augmented human loop, while validated outputs are persisted into Amazon DynamoDB. Documents uploaded to S3 trigger step function workflows that apply confidence-based routing, where high confidence data is propagated to downstream systems and lower confidence items enter the A2I review flow. The processed data is stored in DynamoDB and extracted periodically for ERP integration and downstream accounting consumption.
Implementation and delivery were executed in partnership with MothersonSumi Infotech & Designs Limited MIND, leveraging MIND’s APN incubation engagement with Amazon Textract to accelerate time to production. The serverless design reduced operational overhead by minimizing infrastructure management and allowed a faster rollout cadence. The solution provided the required level of accuracy, reduced operational overhead, and achieved faster time to production as reported by the project stakeholders.
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Max Healthcare Institute | Healthcare | 15000 | $548M | India | Amazon Web Services (AWS) | Amazon DynamoDB | Database Management | 2021 |
In 2021, Max Healthcare Institute implemented Amazon DynamoDB as a central data store within a serverless document processing pipeline to automate supplier invoice ingestion and extraction. MothersonSumi INfotech & Designs Limited, MIND, partnered on the engagement, addressing challenges including multiple invoice templates and high licensing costs that had previously driven a 29 person back office and accounts payable effort across Max Healthcare’s 16 facilities and related Max@Home and Max Labs operations.
The implementation used a serverless architecture built on Amazon S3, AWS Lambda, AWS Step Functions, Amazon Textract, Amazon A2I, Amazon API Gateway, and Amazon CloudWatch, with Amazon DynamoDB providing the Database Management backbone for extracted document data. The pipeline includes a daily scheduler to ingest scanned documents into S3, Step Functions orchestration per document, image pre processing to improve readability, Textract based form and raw data extraction, post processing for template based field validation, and an augmented human review loop via Amazon A2I for low confidence items.
Operational integration centered on feeding validated supplier and invoice data into Amazon DynamoDB, from where records are periodically extracted for entry into downstream ERP and payment systems. The scope of the deployment covered back office and accounts payable business functions across the hospital network, with document ingestion, extraction, validation, human review, and downstream reconciliation articulated as discrete functional workflows.
Governance and runbook controls were implemented through Step Functions orchestration and CloudWatch monitoring, with MIND leveraging its APN relationship for Amazon Textract to accelerate production readiness. The project delivered the stated outcome of achieving the required level of extraction accuracy with minimal operational overhead and faster time to production while centralizing extracted document state in Amazon DynamoDB for Database Management and downstream financial processing.
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Healthcare | 15000 | $548M | India | Amazon Web Services (AWS) | Amazon S3 | Cloud Storage | 2021 |
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Healthcare | 15000 | $548M | India | Amazon Web Services (AWS) | Amazon Textract | Intelligent Document Processing | 2021 |
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