Cloud / AI Finding 002
The cost of waiting during AI inference degradation
AI endpoints can degrade before a visible outage appears.
Audience cto, ai_platform, finops
Dataset reference tenant
Window 30 days
Boundary no customer data
Why this matters
PainAI endpoints can degrade before a visible outage appears.
Decision exposureThe question is not whether a dashboard can show a signal. The question is whether the organization can decide while the decision still matters.
Raven / Mira angleRaven frames the decision window; Mira frames compute burn.
Reference evidence
Observation base1 248 000 synthetic observations across 30 days.
Candidate windows74 candidate decision windows; median candidate window 16 minutes; longest modelled window 23 minutes.
Evidence directionUse latency, queue and GPU-capacity patterns without exposing prompts.
What remains unproven
Customer fitA real customer result requires approved customer records, SLO language, team structure and cost assumptions.
ROIFinancial values remain MODEL or ESTIMATE until the customer validates business assumptions.
ExecutionRaven does not execute cloud action automatically. Human approval remains final.
Next step
Report sampleView the Cloud/AI report demo repository.