Production DevOps and infrastructure capability is crucial because the first major surprise in AI projects is rarely the AI model itself, but rather the data engineering and MLOps scaffolding needed to keep it running. A vendor might show a high-accuracy proof-of-concept, but production deployment can collapse under real data volume without proper operational infrastructure.
Production DevOps and infrastructure capability is crucial because the first major surprise in AI projects is rarely the AI model itself, but rather the data engineering and MLOps scaffolding needed to keep it running. A vendor might show a high-accuracy proof-of-concept, but production deployment can collapse under real data volume without proper operational infrastructure.
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Production DevOps and infrastructure capability is crucial because the first major surprise in AI projects is rarely the AI model itself, but rather the data engineering and MLOps scaffolding needed to keep it running. A vendor might show a high-accuracy proof-of-concept, but production deployment can collapse under real data volume without proper operational infrastructure.
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