AI in the
business world
Artificial Intelligence contributes to improving business performance with solutions that have been developed and trained to perform sophisticated tasks. Until now, these tasks could only be performed by people. AuraQuantic incorporates services such as artificial vision, structured optical character recognition, sentiment analysis, and virtual assistants or chatbots.
BENEFITS
AI for smarter and more sustainable businesses
Cost reduction
Intelligent automation frees up large amounts of employee time, reducing costs and waiting times.
Improving user and employee experience
AI structures information, detects patterns and incidents, seamlessly assists customers and augments employee capabilities when used in conjunction with business rules to offer recommendations in real time.
Risk minimization
AI services and Machine Learning enable the analysis of historical data to detect anomalies, make maintenance and prevention recommendations and automatically develop algorithms to calculate numerical targets or categorize data.
FUNCTIONALITIES
AI solutions to take process automation to another level
Intelligent Document Processing (IDP)
IDP converts unstructured and semi-structured data into useful data, with tools such as data capture, classification neural networks, Optical Character Recognition (OCR) and continuous monitoring to improve the accuracy of AI models.
Cognitive services
The development of no-code applications and workflows that incorporate cognitive features for text classification, sentiment detection or keyword extraction.
Intelligent virtual assistant
The AI-based solution automates communication, provides a seamless customer service channel and facilitates information search.
Artificial Vision
The extraction and analysis of information contained in digital images, videos and other visual resources to make recommendations. It can also be part of other processes such as document classification and detection.
Machine Learning solutions
Algorithms that can be generated automatically, learn from data, and improve their level of accuracy with new data, which are used to classify and provide numerical targets.
AI anomaly detection
Analysis of data sets from different sources to identify anomalies and take corrective actions.
