Capability layer: AI models
Models developed and fine-tuned for the tasks they perform.
The model is one part of a system Sheba also runs, never a product on its own. Sheba builds models and fine-tunes them for the use case they will serve inside its products and the deployments it operates.
The work itself
The model is fine-tuned on data that represents the use case, then placed in the system it was prepared for. What that data has to represent is settled first: the requests the model will meet, and the language they arrive in.
Work may involve developing a model or fine-tuning an existing one, depending on the data, task and system requirements.
Languages and dialects
Part of fitting a model to a use case is fitting it to the language, and the dialect, its requests arrive in.
One example of this work
One market, and a model built for it
It runs inside Sheba’s systems rather than on its own, and it shows what this layer means in practice.
Where the models run
None of them is offered on its own, because each was fitted to work inside a particular system: a Sheba product, or a deployment Sheba builds and operates.
Choosing and routing between models
Sheba Enterprise Platform manages model access and request routing by task. It is a production-ready product with access starting through evaluation.
See how the platform routes modelsFAQ
What people ask about the model work
Whether your use case needs a fine-tuned model is the first thing to find out.
Scoping the model work comes before any estimate, and it starts from the use case you describe.
Discuss model work for your use case