We craft software, platforms and technology solutions for companies across the world, ranging from startups to Fortune 500 companies. We are backed by a group of experts with deep industry and technology expertise who can help with not only development but also launch and scaling.
We have clients in over 15 countries including Argentina, Canada, Denmark, Germany, India, Indonesia, Malaysia, Mexico, Nigeria, Norway, Pakistan, Russia, Switzerland, UK and USA .
How can we help you ?
Canada: +1 (647) 948 6721
Pakistan: +92 423 5831257
Our AI and Machine Learning solutions improve organizational productivity and operational efficiency by automating processing intelligently - reducing manual intervention.
Our NLP based algorithms will work with large set of structured data to extract insightful information. NLP can help in training chatbots and other AI based solutions.
We develop ML models which increase productivity, reduce costs and minimize human intervention using a secure robust platform.
We mine data from around the web by leveraging our advanced data mining tools. With have proven excellence in delivering comprehensive web data mining for your analysis team.
Using AI, we have developed smart IoT solutions which provide meaningful insights in data.
Using web scraping and machine learning - we use structured data sets to predict values - for example pricing of automobiles using make, model, trim and condition.
Our AI based chatbots use NLP and Machine Learning algorithms to provide full automated and seamless customer service.
There is a close relationship between the subfields of computer science known as artificial intelligence and machine learning. These two technologies are currently at the forefront of technological advancement and are utilised in the production of intelligent systems.
Despite the fact that these are two related technologies and some individuals do use them interchangeably, they are nonetheless considered to be two distinct concepts in a number of contexts.
Artificial Intelligence (AI)
The subfield of computer science known as artificial intelligence is concerned with the development of software that can simulate human intelligence. It is a combination of the words “artificial” and “intelligence,” which together signify “a thinking capability that has been manufactured by humans.” Because of this, we can say that it is,
Through the use of a technology known as artificial intelligence, we are able to develop intelligent systems that are capable of simulating human intelligence.
Machine Learning (ML)
The process of extracting knowledge from data is at the heart of machine learning. It is possible to describe it as,
Machine learning is an area of artificial intelligence that enables machines to learn from previous data or experiences without being explicitly programmed to do so. This was made possible by the development of deep learning algorithms.
The combination of artificial intelligence, machine learning, and deep learning provides businesses with a means to derive value from the mountains of data they amass by giving actionable business insights, automating processes, and expanding system capabilities.
Artificial Intelligence (AI)
The artificial intelligence system does not need to be pre-programmed; instead, it makes use of algorithms that are able to function using its own intelligence. It makes use of machine learning methods such as the reinforcement learning algorithm and deep learning neural networks, among others. There are a variety of applications for artificial intelligence, such as Siri, Google’s AlphaGo, using AI to play chess, etc.
There are three distinct types of artificial intelligence, each distinguished by the characteristics they offer:
Weak AI
General AI
Strong AI
Machine Learning (ML)
Without being specifically programmed, a computer system can learn how to anticipate the future or make certain decisions by analysing previous data through the process of machine learning. In order for a machine learning model to accurately create results or make predictions based on the data it has access to, machine learning requires a significant amount of data that is either fully or partially organised.
The algorithms that power machine learning are designed to discover new information on their own by analysing past data. It is only applicable to certain fields; for example, if we are developing a machine learning model to identify photographs of dogs, the model will only return accurate results for canine photographs; but, if we add additional data, such as a cat photograph, it will stop responding to our input. Machine learning is currently being utilised in a wide variety of contexts, including online recommender systems, the search algorithms used by Google, email spam filters, Facebook’s auto friend tagging suggestion, and many more.
It can be broken down into the following categories:
Supervised learning
Reinforcement learning
Unsupervised learning