Your models.
Choose the model for the task.
Compare open models and provider APIs against your requirements. Keep the evaluation separate from any one provider, so a new model can be assessed on the same work.
OUR APPROACHAI that learns
AI that learns
from your work.
Own your intelligence means keeping control over the parts that shape how AI works for your business: the model, the data, the deployment and the decision to change it.
Your data.
Set the terms for its use.
Agree which information the system may access, where it is processed and whether it can be used for improvement. Data access and training permissions are separate decisions.
Your deployment.
Agree where the work runs.
For a model deployed on agreed infrastructure, define the region, storage, networking and operating responsibilities. For provider APIs, check the processing locations and controls the provider makes available.
Your releases.
Approve changes you control.
Compare proposed changes with the current setup before release. Agree rollback and operating responsibilities. Changes to an external API’s models or service follow the provider’s release and retirement policies.
THE IMPROVEMENT PROCESSKeep what
Keep what
you learn.
A model can change. Your evaluation tasks, approved examples and operating knowledge should remain useful when it does. The process below is a proposed way to organise that work.
FROM EXPERIENCE TO A TESTED CHANGEIllustrative process
Start with a real task.
Choose work your team knows well. Record what a good result looks like, where the current setup fails and which examples you have permission to use.
↳ Reviewed results inform the next test. Changes go live after review.
CHOOSE WHAT FITSOpen models.
Open models.
Provider APIs.
A reason for each.
An external model API may be the right choice for a demanding task. A specialised model may be worth evaluating when you have a repeatable workload and suitable data.
We compare the options on the work that matters to you. Model licences, provider terms and data permissions determine the rights available in each setup. Control over a deployment does not imply ownership of a third-party base model.
Evaluation and model improvement ↗LET'S START WITH THE WORKWhat do you
What do you
need to run?
Tell us about your application, the models you use and the capacity you need. Estimates and open questions are welcome.
Prepare a workload brief ↗Non-sensitive information first. Current customer outreach focuses on US customers.