20h • Challenge
ProDiag AI - Day 7 Progress
Day 7 — ProDiag AI | From Local Prototype to Production Architecture 🚀
Today was less about adding another UI feature—and more about making the system deployable, reliable, and production-oriented.
I containerized the ProDiag AI V2 backend with Docker and validated the complete communication architecture:
React Frontend → Flask Backend → MQTT/TLS → HiveMQ Cloud → Industrial Simulator
The backend now includes the trained ML models, RAG components, knowledge base, and MQTT services inside a deployment-ready container.
I also fixed an important initialization issue discovered during container testing: the database schema must be created before services such as the Alert Service attempt to load existing records.
This is exactly the kind of issue that doesn't always appear during local development—but becomes critical when moving toward production.
Building an AI system is not only about the model.
The real challenge is making the entire system work together reliably.
#AI #IndustrialAI #PredictiveMaintenance #AgenticAI #MachineLearning #IIoT #Docker #MQTT #Engineering #ProDiagAI
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ProDiag AI - Day 7 Progress
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