Document intelligence in regulated workflows: extraction with verification
Extracting data from documents with AI is easy to demo and hard to trust. How to build extraction with validation, confidence and human review.
Articles tagged Production Readiness.
Extracting data from documents with AI is easy to demo and hard to trust. How to build extraction with validation, confidence and human review.
How to use AI agents in enterprise workflows safely: bounded tools, read-before-write, explicit approvals and an audit trail of every step.
Why we describe applications in three stages (deployment-ready foundation, customer-configured, production deployment) and never call a template 'production'.
Series: The Application Factory
AI features need evaluation as a delivery gate, just like tests: test sets, groundedness checks, safety checks and regression on every change.
Most enterprise AI pilots never reach production. The gap is not the model. It is identity, integration, controls, evaluation and ownership.
Series: The Application Factory
Our developers already have AI coding tools, so why use fazeZERO? The answer is not better AI. It is the architectural system the AI works inside.
Series: The Application Factory
Why fazeZERO uses AI inside a proven production architecture instead of letting it improvise a new architecture for every enterprise application.
Series: The Application Factory
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