Custom machine learning model development

A model trained on your data for one task, proven against a baseline before you rely on it.

For CTOs, product owners and data teams with their own data and a task they can measure.

Our custom machine learning model development starts by defining what good looks like as a number. We test existing models against it and train on your data only where that does better.

eORB Solutions Inc provides custom machine learning model development for CTOs, product owners and data teams with their own data and a measurable task. We define the measure, test existing models as a baseline, and train on your data only where it does better. Speed and running cost are agreed in writing, and your team stays in control.

When is a general-purpose model not accurate enough?

When it gets your task almost right, and almost right is not good enough. Your own data could close the gap, but no one is using it.

What does custom machine learning model development include?

  • The measure first

    What good looks like, defined as a number before any training starts.

  • A baseline to beat

    We show where existing models fall short on your task before we train anything.

  • Trained on your data

    Images, text or sensor data, kept in your cloud account or one we set up in your name.

  • Fast and affordable to run

    Response time and running cost agreed in writing, monitored, and kept on target through scheduled retraining.

Your first two weeks

By the end of week two you have the agreed measure, the baseline result and a first trained result on your own data. You see whether a custom model is worth pursuing before you commit further.

What comes after

Full training and evaluation

The model trained on your full data set and tested against the agreed measure.

Serving and monitoring

The model running at the agreed speed and cost, with its accuracy watched in production.

A retraining schedule

Regular retraining on new data, so accuracy holds as your business changes.

Integration into your product

The model connected to your applications through documented APIs.

Questions buyers ask

How much data do we need?
Often less than expected, but it depends on the task. We review a sample of your data before any commitment and tell you whether it is enough, what is missing and how to collect it. The first two weeks then test that view against a real result.
Where does it run, and who owns it?
It runs in your cloud account, or in one we set up in your name. You own the model, the code and the data from the first week, and your data trains only your model. Access and storage location are agreed in writing first.
What if an existing model is good enough?
Then we tell you, and you keep it. The baseline is there to make that call honestly before you spend on training. Some tasks are better served by an existing model with clear instructions and your documents, and we say so when that is the case.
Who stays in control?
Your team does. The model's results are monitored against the agreed measure, and people decide how its outputs are used in your product or process. If accuracy drifts below the agreed level, your team is alerted and the model is retrained or rolled back.
What does it cost?
It depends on scope. The main factors are the data, the task, how quickly the model must respond and the volume of requests it will handle. Share your website and we'll come back with a clear plan and a written estimate.

Start with the measure, then the model