Insights

Technical writing
from production.

What we have learned building data infrastructure, cloud systems, and AI deployment for healthcare, agriculture, and manufacturing operations teams.

Five articles on data infrastructure, cloud engineering, and AI deployment. Written from production engagements, not from documentation.

Data Infrastructure/Cloud Engineering/AI Deployment
All posts
Data Infrastructure9 min read
March 14, 2026

EHR Data Integration: What Actually Breaks in Production

FHIR APIs, HL7 feeds, and billing systems look straightforward in testing. Here are the five failure modes that appear only after go-live, and how to design around them.

By Kinesiis Engineering Team

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Cloud Engineering10 min read
March 14, 2026

HIPAA-Compliant AWS: What an Audit Actually Checks

AWS's HIPAA-eligible services list is not a compliance checklist. Here is what auditors actually examine, and the gaps we find most often in healthcare AWS environments.

By Kinesiis Engineering Team

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AI Deployment8 min read
March 14, 2026

Why ML Models Don't Survive the Move from Notebook to Production

The model performs well in testing. Six months later it's still in the notebook. Here are the four reasons AI pilots fail to reach production, and what production-ready deployment actually requires.

By Kinesiis Engineering Team

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Data Infrastructure7 min read
March 14, 2026

Agricultural IoT Data Pipelines: The Connectivity Problem Nobody Talks About

Farm IoT data pipelines fail for reasons that don't appear in industrial IoT textbooks. Intermittent connectivity, power constraints, and device heterogeneity create failure modes that require different architectural decisions.

By Kinesiis Engineering Team

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Data Infrastructure7 min read
March 14, 2026

The Real Cost of a Broken Data Pipeline in a Hospital Network

The obvious cost of a broken hospital data pipeline is delayed reports. The less obvious costs are larger. Here is what manual data reconciliation actually costs a multi-site network, and why the business case for fixing it is usually stronger than IT teams expect.

By Karan Bhosale

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Data Infrastructure8 min read
March 19, 2026

Building In-House vs Hiring a Specialist for Healthcare Data Infrastructure

Your IT team knows the data pipeline is broken. The question is whether to pull someone off BAU work to fix it or bring in outside expertise. Here is how to think about that decision.

By Karan Bhosale

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Data Infrastructure7 min read
March 19, 2026

Why Most Data Infrastructure Pilots Never Reach Production

The pilot impresses the executive team. The project gets funded. Then it sits in staging for eight months. Here is why data infrastructure pilots stall, and what production-first engagement looks like instead.

By Karan Bhosale

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Data Infrastructure8 min read
March 19, 2026

Why Manufacturing Data Projects Stall Between the Historian and the Dashboard

Most manufacturing data initiatives die in the gap between extracting data from historians and SCADA systems and delivering something operations teams will actually use. The technical and organisational reasons are predictable and avoidable.

By Karan Bhosale

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Cloud Engineering7 min read
March 19, 2026

Store-and-Forward vs Real-Time: Choosing the Right IoT Architecture for Agriculture

Real-time IoT architectures work in factories with reliable connectivity. On farms, they lose data. Here is how to choose between store-and-forward and real-time ingestion for agricultural operations, and when you need both.

By Kinesiis Engineering Team

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Cloud Engineering9 min read
March 19, 2026

AWS vs GCP for HIPAA-Compliant Healthcare Infrastructure

Both AWS and GCP can meet HIPAA requirements. The differences that matter are in managed service coverage, audit tooling, and how your team will operate the environment after handover.

By Karan Bhosale

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Web Development8 min read
March 19, 2026

Custom ERP Integration vs Off-the-Shelf Connectors for Manufacturing Websites

Off-the-shelf ERP connectors promise to display live product availability on your website in days. In practice, they work for simple catalogs and break for everything else. Here is how to evaluate whether a connector will work for your product catalog or whether you need a custom integration.

By Karan Bhosale

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