ONE SOLUTION, WIDE VARIETY OF TASKS
ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING PLATFORM
Machine Learning is not magic. Artificial Intelligence is not yet capable of resolving all tasks set by human beings. So, how can we offer a single platform for such a wide variety of tasks?
The ENAIA Artificial Intelligence and Machine Learning platform uses different types of technologies depending on the issues raised by the client. Thanks to its R+D, ENAIA has pipelines that standardise the training workflows for each task. These pipelines reduce ENAIA’s implementation and make it possible offer highly competitive prices that are proportional to the size of the customer’s business.
Why don’t we focus on
one type of task?
A very large percentage of the development for a Machine Learning-based solution can be standardised, independently of the type of task. The aim of ENAIA is to strengthen processes that are common to all of them and focus on what is really important: a tool that allows humans to teach AI continuously, in other words, a “living” technology.
Developed by Neuraptic
As researchers, we are working to include the latest progress from the scientific community and focus our technology on the future.
Our Artificial Intelligence’s training technology saves supervision time (labelling the data) for the customer and accelerates implementation.
AI makes predictions using the input data. ENAIA can work with pictures, natural language, data tables, and combinations of all three.
Use of ENAIA does not require writing code. It has been developed so that any developer can integrate it easily into their company’s user systems using a REST API interface. The ENAIA graphic interface makes it possible for any user to operate the platform “in just a few clicks”.
The AI uses the unlabelled data (without customer supervision) to build internal representations that help it become familiar with the task. This helps it learn faster (less supervision).
The AI helps the customer during their supervision using specific questions on the data: Is this a fault? Is this really a grease stain? I am confused about the difference between oranges and satsumas… This allows the AI to focus on the complicated cases (raising the most doubts) and thereby reduce the quantity of data to be labelled.
AI is continuously learning and improving while it is working, allowing it to maximise the performance from the applied Artificial Intelligence solution.
ENAIA continuously supervises the AI inputs and outputs to detect anomalies in how the model is working. A system of alarms sends notifications to the users responsible for each task when they occur.
ON THE EDGE
The AI trained by ENAIA can be deployed in production environments that are not connected to the internet. In these cases, predictions are made locally.