Model productization
What should a research team prepare before productizing a model?
A practical starting checklist, from runnable code to acceptance examples.
Start with one concrete use case
Describe who uses the model, which input they provide and which output they need. A frequent task with inspectable results is a better starting point than an entire platform.
For example, an image-model project could cover a single input, one model call and one result view. Batch processing, collaboration and ongoing operation can be scoped separately. This is a scoping example, not a promise that every model can be deployed this way.
Prepare reproducible materials
- Code, dependency versions, access to weights and permitted uses.
- Examples that may be used for development and acceptance testing.
- Expected outputs, known failure modes and evaluation methods.
- Hardware requirements, observed runtimes and current operating instructions.
If only a paper exists, reproduction and feasibility come first. Reproduction is a distinct task from interface development.
Separate model quality from engineering usability
Domain-specific methods assess model quality. Engineering review also covers input constraints, failure messages, deployment instructions and handover. Agree examples and excluded features before implementation.
Bring practical constraints to the discussion
Who will use the tool? Must it run on campus? Who provides compute and maintains it? These answers inform the API, interface and deployment scope.