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Local-First AI Inference: A Cloud Architecture Pattern for Cost-Effective Document Processing
The Local-First AI Inference pattern routes 70–80% of documents to deterministic local extraction at zero API cost, reserving Azure OpenAI calls for edge cases and flagging low-confidence results for human review. Deployed on 4,700 engineering drawing PDFs, it cut API costs by 75% and processing time by 55%, while bounding errors through a human review tier.
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Secure AI-Powered Early Detection System for Medical Data Analysis & Diagnosis
In this article, the author discusses the techniques for securing AI applications in healthcare with an use case of early detection system for medical data analysis & diagnosis. The proposed layered architecture includes application components to support secure computation, ai modeling, governance and compliance, and monitoring and auditing.