Best architecture for enterprise knowledge assistants
Production AI needs its own operational discipline.
We normally plan for versioned prompts and models, traceable inputs and outputs, evaluation datasets, latency and cost monitoring, fallback paths and rollback procedures. The exact stack varies, but these controls make experimentation compatible with reliable software delivery.
An overview of our work is available through AI Development Services. The complete delivery scope is described at https://ai-development-services.com, and our <a href="//ai-development-services.com">production AI engineering overview</a> explains how these operational controls fit into implementation.
Which observability signal has helped you catch failures that standard application monitoring missed?
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