Reliability
An AI agent that's right 95% of the time is an agent that's wrong in 1 out of every 20 decisions. In banking, that's unacceptable.
"AI reliability is not uptime. It is predictability. And predictability is what sustains trust."
4requirements · aiuc-1.com.br
An AI agent that's right 95% of the time is an agent that's wrong in 1 out of every 20 decisions. In banking, that's unacceptable.
AI reliability isn't measured by uptime. It's measured by output consistency under input variation.
What the market believes
The market measures AI reliability like SaaS reliability: uptime, latency, SLA. But an agent can be 100% online and produce inconsistent results.
The same question asked twice can generate different answers. In compliance, consistency isn't a feature. It's a requirement.
What AIUC-1 requires
Output consistency. Performance under load. Fault tolerance. AI-specific reliability metrics, not borrowed from infrastructure.
Keywords
UptimeFault ToleranceConsistencyIn practice
Define what "consistent" means for each use case. If the compliance agent answers differently for the same regulatory question, the problem isn't the model. It's the absence of acceptance criteria.
AI reliability is not uptime. It is predictability. And predictability is what sustains trust.