In order for algorithms to operate reliably, they need to be managed separately. The Algorithm Factory makes sure that managing a thousand algorithms is as easy as managing just one.
Let your data define the right algorithm and train thousands of individual algorithms automatically.
Each individual algorithm needs to be trained on its data and context. Otherwise, they won’t be accurate. Even if you only have a few algorithms, training takes time and effort.
The Algorithm Factory tackles this with mass customisation. This allows you to:
Get speed, security and scale for the lowest price possible. Obtain the best algorithm run-time in the market.
In order to solve for a particular problem, you need to choose the right algorithm and the right dataset. With more algorithms, this can become a complex exercise.
The Algorithm Factory makes this as easy as it should be. It does so by:
Beat quality deterioration due to changing realities. Automatically perform quality checks and retrain.
Because environments change, algorithms lose their accuracy over time. You need to monitor their output and compare it with the actual output. If inaccurate, they need to be retrained on a new dataset. This monitoring, comparing and retraining is usually a manual process.
The Algorithm Factory, however, ensures your algorithms’ results are accurate. It does so by:
Connect your data and system to the Algorithm Factory to start training, running and managing algorithms.
Easily pick which services you like to use thanks to our microservices architecture.