Observing AI Answers: How to Handle Variability in Model Outputs
Explains the definition and need for AI observation, how it works, and criteria for applying SAG architecture and practical checklists, drawing on research and official documentation.
SAG TECHNOLOGY FRONTIER
We do not follow the curve.
SAG builds what comes next.
We design how search, answers and generative AI understand brands, and explain the architecture behind SAG in clear technical terms.
SAG / ARCHITECTURE NOTES
Five principles behind SAG today
From discovery and evidence to data boundaries, reliable execution and delivery—see how each engineering choice works.
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