Production Readiness Assessment
A go / no-go verdict on whether your AI system is actually ready for production — not just a demo that worked once.
Delivery: Remote, worldwide
The problem
A system that works in staging, or even in a limited pilot, doesn't automatically survive real production load, real failure conditions, or a real cost curve. Teams often find out the gaps — a missing retry path, an unbounded cost query, an unmonitored failure mode — only after they've already shipped.
Who this is for
Teams about to move an AI system from pilot to general availability
Founders who need an independent go/no-go opinion before a launch
Engineering leaders who suspect reliability or cost debt but lack the bandwidth to verify it themselves
Technical scope
Deliverables
A clear go / no-go verdict, not a vague risk score
A prioritized list of what has to be fixed before launch versus what can wait
A walkthrough call to discuss findings with your team
FAQ
What's the difference between this and an Architecture Review?
An Architecture Review evaluates the design across all ten pillars. This is narrower and go/no-go focused: is this specific system, as it stands today, safe to put in front of real users.
What do you check for reliability?
Failure handling, retries and graceful degradation, load behavior, and whether the system has been tested against realistic failure conditions rather than only the happy path.
Can this be done before a launch deadline?
Scope and timeline are agreed before the engagement starts based on system complexity — get in touch to discuss your specific timeline rather than assuming a fixed duration.
About to ship an AI system to real users?
Get an independent go/no-go before launch day, not after.