Custom machine learning
Models that predict what’s next, trained on your data
We train models on your historical data to anticipate demand, catch anomalies early and automatically classify what is reviewed by hand today. And before building, we validate that your data is enough, so the project starts on solid ground.
What it solves
If any of these three sounds familiar, this is your door.
Inventory and purchasing calls are made on instinct, and the misses are expensive.
Somebody reviews thousands of records by hand looking for the few that are wrong.
Years of data are sitting there being used for nothing.
What we build
The full scope, with no small print.
- 01Prediction on your historical series
- Demand, churn, credit or attrition risk. With the seasonality and the odd events of your own business, which a generic model has never seen.
- 02Anomaly and fraud detection
- Learned from how your operation normally behaves rather than from a fixed rule. That is what surfaces the things nobody thought to look for.
- 03Automatic classification
- Documents, tickets, images or records somebody sorts by hand today. With a confidence threshold: the doubtful ones go to a person instead of being decided badly.
- 04Computer vision
- When the data arrives through a camera: counting, quality control, plate or label reading.
- 05Scheduled retraining
- A model that is not updated degrades on its own, because the world it learned stops existing. It is left scheduled, with an alert for when accuracy drops.
How it is done
- 01
Feasibility on the data you have
Before quoting the build we check whether the data is enough. If it is not we say so there, and the project becomes collecting it properly.
- 02
Training and honest measurement
Measured against a period the model never saw, and reported together with where it fails. A model without its failure cases documented is not finished.
- 03
Put where the decision happens
The prediction lands on the screen where somebody decides. A model living in a separate report changes no decisions.
What you get
What stays in your hands when the project ends, with or without us afterwards.
The model in production, wired to where the decision gets made.
An honest measurement of how often it is right and where it fails.
The retraining process and an alert for when performance drops.
Documentation of the data it consumes and the assumptions it makes.
We anticipate what’s coming from your own data.
Frequently asked questions
How much data do we need?
It depends on the problem, and it is the first thing we validate before quoting.
Can we know why the model decided that?
Yes: where decisions must be justified, we use explainable models from the design stage.
How is this different from an agent or a chatbot?
The model predicts or classifies; the agent or chatbot acts and converses. They often work together.
Not sure which AI solution fits your company?
Book a free consultation with the team. No sales pitch: we tell you honestly how, and whether, artificial intelligence actually helps your operation.
Who you talk to
- 20 years building technology
- More than 10 companies of our own built
- Custom projects in any industry