Production AI application
Take a proven use case to production: build the application, set up the infrastructure, deploy it, instrument it, and hand it over to a named owner.
Timeline agreed with scope. Fixed price agreed before work starts.
What you receive
- The application built in your environment, under accounts and repositories you control
- Infrastructure set up for it, with a repeatable deployment pipeline
- Tests for expected results, failure modes, and the limits that keep usage and cost in bounds
- Monitoring, logging, and cost controls your team can read without us
- A runbook covering operation, rollback, and known limitations, and a handover session with the owner
Scope and limits
Scope covers one application and the named systems it connects to. We agree access, acceptance checks, release responsibilities, and where human review stays in the loop before work starts. Ongoing operation and support after handover are scoped separately.
When this is not the right engagement
If the use case has not been tested on your data yet, start with a proof of concept. Building for production around an unproven idea costs more than finding out first.