Developing AI Solutions For Your Industry

Finance

  • Financial Analytics
  • Credit Scoring
  • Fraud Detection
  • Smart Advisors and Personalized Management
  • AI Insurance

Travel

  • Customer Segmentation and Personalization
  • Dynamic Pricing Solutions
  • Sentiment Analysis
  • Demand Forecasting
  • Intelligent Travel Assistants

E-Commerce

  • Sales Forecasting
  • Personalized Shopping
  • Recommendations Fraud Detection
  • Customer Support Automation and Chatbots
  • Voice Assistance

Transportation

  • Optimized Routing and Scheduling
  • Smart Fleet and Staff Management
  • Vehicle Maintenance Prediction
  • Traffic Prediction and Real-Time Updates
  • Supply Chain Automation

Healthcare

  • Diagnostics Automation
  • Personalized Healthcare
  • Identifying At-Risk Patients
  • AI-Driven Pharmaceutical Research
  • ML for Clinical Data Analysis

Retail

  • Supply Chain Planning
  • Inventory Management
  • Price Optimization
  • Market Basket Analysis
  • Market Basket Analysis
PIC

Deep Learning Vs. Machine Learning

Since deep learning and machine learning tend to be used interchangeably, it’s worth noting the nuances between the two. As mentioned above, both deep learning and machine learning are sub-fields of artificial intelligence, and deep learning is actually a sub-field of machine learning.

Artificial Intelligence Applications

There are numerous, real-world applications of AI systems today. Below are some of the most common examples

Speech recognition

It is also known as automatic speech recognition (ASR), computer speech recognition, or speech-to-text, and it is a capability which uses natural language processing (NLP) to process human speech into a written format. Many mobile devices incorporate speech recognition into their systems to conduct voice search—e.g. Siri—or provide more accessibility around texting.

 

Customer service

Online chatbots are replacing human agents along the customer journey. They answer frequently asked questions (FAQs) around topics, like shipping, or provide personalized advice, cross-selling products or suggesting sizes for users, changing the way we think about customer engagement across websites and social media platforms. Examples include messaging bots on e-commerce sites with virtual agents, messaging apps, such as Slack and Facebook Messenger, and tasks usually done by virtual assistants and voice assistants.

Computer vision

This AI technology enables computers and systems to derive meaningful information from digital images, videos and other visual inputs, and based on those inputs, it can take action. This ability to provide recommendations distinguishes it from image recognition tasks. Powered by convolutional neural networks, computer vision has applications within photo tagging in social media, radiology imaging in healthcare, and self-driving cars within the automotive industry.

Recommendation engines

Using past consumption behavior data, AI algorithms can help to discover data trends that can be used to develop more effective cross-selling strategies. This is used to make relevant add-on recommendations to customers during the checkout process for online retailers.

 

Automated stock trading

Designed to optimize stock portfolios, AI-driven high-frequency trading platforms make thousands or even millions of trades per day without human intervention.

Our Distributing Partners

We have agency / distributorship agreements with a selection of reputed companies for marketing, distributing, selling and servicing of their products in the GCC countries.