Artificial Intelligence.

An AI(Artificial Intelligence) enabled model is a practical application/machinery/automated tool that works on the core linings of AI. 

When the software structure of AI is enabled in the hardware of an automated tool, to reduce costs, automate procedure or any other reason, that coalition is known as an AI model. 

Many approaches are used to build an AI. These approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools and methodologies are used in AI, including versions of search and mathematical optimization, artificial neural networks, and methods based on statistics, probability and economics.  

We train and deploy customized Deep Learning (DL) models to provide solutions for businesses and allow them to stay ahead of the curve.  Our team of Machine Learning (ML) experts and data engineers leverage the state-of-the-art models and techniques in DL and latest software development processes including SCRUM to deploy Artificial Intelligence

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Predictive Maintenance

Machine learning to analyze operations data to determine the condition of equipment and machinery to prevent failures. 

We provide expertise for AI projects within Cloud platform for multiple business sectors such as  aerospace, automotive industry and Industrial systeme.

Healthcare

Our machine learning team provides the best services to the healthcare industry. YaiGlobal Provides this services by including functionality specific to healthcare, as well as simplifying the workflow of creating and deploying models.

We provide expertise for AI projects within Cloud platform for multiple business sectors such as  aerospace, automotive industry and Industrial systeme.

Patern Recognition

Images or visual data typically carry a lot of information that cannot be easily accessed using traditional image processing techniques. 

DL has shown tremendous success in image analytics using Convolutional Neural Networks and other architectures.

At YaiGlobal, we will develop and deploy latest DL techniques to extract relevant information from images of interest. 

Prediction

Predicting and forecasting stock market prices is one of the pillars led by AI. Stock market prices are highly affected by several inputs such as overall market, supply and demand, economic environment, corporate decisions, and stock market itself.

Our team is working on predicting these values for digital currencies, one in particular, Bitcoin. Our team is working on training models to detect several correlations and features with various data sets.

Building the model using deep learning applied on various dataset. Each dataset (such as market historical data, external events, media input, etc) each data set trains a separate model, for taking into consideration all entrants affecting Bitcoin Market value.

Use Cases

Natural Language Processing from social media comments to feedback analysis

During this digital transformation era many companies trusted social media to convey their messages to advertise good, but Digital allows way further producer/consumer interaction than traditional advertising media known in the past.

Consumers comment, give their opinion, give suggestions, express their need etc on social media. He who listens more gets best feedback to improve, adjust and reach the targeted market share.

Our team is working on developing a model to predict sales forecast based on social media input regarding brands and products. The model works by detecting comments for emotional analysis and predict impact based on past impact on social media.

The model is trained using historical sales data and historical comments published on social media around the brand, and when applicable its competition’s related social media comment to adjust to market segments.

Content Classification

Our machine learning approach helps in classifying data in different classes based on customer preferences and data content.  

Nowadays most businesses have massive inflow of social content every day including tweets, posts, blogs and more. Classifying such a social content and preparing it for further processing and analysis will pay dividends to identify pros and cons of business products from a customer perspective.

Information Extraction

Our algorithms can dig up pieces of information like keywords and web links to create a personalized experience for the user.  

Our approach helps obtaining intelligence about what content users are likely to follow and read based on their interests thus giving businesses closer insights to push articles on topics of interest to customers.