Production AI
AI that works in a demo and AI that survives production are two different engineering problems.
What production-ready AI means
An AI system is production-ready when it holds up under real load, real users and real failure conditions — not just a controlled demo. That means it's secure, observable, reliable under failure, cost-predictable and governed, in addition to functionally correct. Most of the gap between an AI prototype and a production system isn't the model — it's everything engineered around it.
What changes on the way to production
The method
Every system is reviewed against the same ten pillars — see the full breakdown in the Production AI Architecture Standard, or get it applied to your own system with a Production Readiness Assessment.
Related expertise
Evidence
FAQ
What does production-ready AI actually mean?
An AI system is production-ready when it holds up under real load, real users and real failure conditions — not just a controlled demo. That means it's secure, observable, reliable under failure, cost-predictable and governed, in addition to functionally correct.
What's the difference between a POC and production AI?
A POC proves an idea works once, in a controlled setting. Production AI has to keep working under real traffic, handle failures gracefully, stay within a cost budget, remain observable when something goes wrong, and satisfy governance requirements — none of which a POC is built to do.
How do you assess production readiness?
Against the same ten pillars used for every architecture review. See the Production Readiness Assessment for the engagement.
Have an AI system about to meet real traffic?
Find out what stands between prototype and production before your users do.