Typical problems
- The prototype only works in the demo
- Tests, error handling, documentation, and deployment safety are missing
- The team does not know whether to keep building or rebuild
Make AI prototype production-ready
The path from demo to product is not more prompting. It requires clean data flows, clear failure cases, security basics, tests, deployment readiness, and maintainability.
Process
The most important user and payment flows are defined.
Build, tests, configuration, failure cases, and security basics are prioritized.
The project becomes easier to understand for further development or operation.
Matching packages
For prototypes that almost work but are not reliable yet.
Triage plus up to ten hours of targeted repair and stabilization.
When an AI prototype needs to become a real product.
Multi-day cleanup for architecture, security, tests, and deployment readiness.
Ongoing senior control while you continue developing with AI.
Monthly allowance for reviews, small fixes, and technical guardrails.
FAQ
No. It means the most important technical risks are reduced deliberately. The exact scope depends on the state of the project.
Deployment readiness is part of production rescue. Whether a live deployment is included depends on the project.
The stabilization sprint repairs core errors. Production rescue goes deeper into architecture, tests, security, and handover.
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