In any competitive business climate, the need to constantly innovate, learn and adapt is crucial to success.
Artificial intelligence (AI) and machine learning (ML) are areas that we recognise are key to tackling existing and future industry challenges. Within this in mind, there are two important critical-systems tasks that are becoming increasingly difficult to process using traditional approaches, and for which AI techniques are far more suitable.
The first task is being able to more intelligently analyse data and information in order to provide more accurate, objective and predictive insights, and to reason more effectively with such information. This allows users to better manage systems with an ever-growing amount of data and information, which humans alone are not as good at undertaking. Several areas of our AI expertise can help with this:
- Machine learning and data mining
- Natural language processing (NLP) and text mining (TM)
- Knowledge representation and reasoning (ontologies)
- Case-based reasoning
The second main area is finding information. Several recent studies have suggested that at least 25% of our time is spent looking for information. In a data-rich and increasingly connected world, with a growing amount of information at our disposal, this is an important challenge to overcome. This is even more important within the scope of critical systems, where the need to find the right information at the right time is often crucial. In tackling these challenges, we offer our expertise in:
- Natural language processing for QA and chatbots
- Knowledge representation and reasoning (ontologies) for information browsing
- Information retrieval and semantic search systems
- Recommendation systems
Reports and Dashboards on Demand
Our chatbot analytics engine is able to answer complex business questions on demand, rapidly gathering the kind of information and KPIs that managers and execs need. Our engine can be integrated into several different communication channels, including Skype and Windows Messenger. Fully customisable, it can also be integrated with several data sources, is fully-scalable, and is easy to setup and maintain.
When Access to Business Information is as Easy as Asking
The ability to provide up-to-date KPIs and on-demand answers to daily business questions is critical to the success of modern organisations. We offer a natural language (NL) search for business intelligence (BI) solution that combines intuitive voice and text requests, giving users the ability to query data and ask questions about information relevant to their business.
Our solution can be integrated with several different data sources without the need to first import data into a single point of access. It’s intuitive and easy-to-understand interface instantly provides businesses with the right information at the right time – whether they are visiting their clients, engaged in board meetings or working on the move.
Taking Business Automation to the Next Level
Automating business processes continues to deliver greater levels of efficiency, allowing humans to spend their time more productively on tasks for which they are better suited. Despite this, the kind of process automation technologies used by businesses today are becoming very common, and cutting-edge organisations are already looking for the next big thing to get ahead of their competitors. This next thing is machine learning, AI and cognitive computing, which promise to take automation to the next level by providing software ‘robots’ that operate like super-efficient humans. These technologies have the power to deal with multiple business processes at once, as well as being able to handle more general tasks and contexts than previously possible.
We offer services that utilise intelligent Robot Process Automation (iRPA) technologies. These services range from an initial situation assessment of a business’ existing processes through to the overall development and implementation of a full iRPA strategy.
Giving Data the Power to Drive Business
Most companies have huge amounts of historical data stored across multiple systems. However, this data is often under-utilised or trapped in legacy systems, preventing businesses from taking full advantage of it. Making proper use of customer information stored across multiple systems is something that almost all of a company’s internal departments could benefit from, in order to improve their services and maximise revenues. Most of the time, however, this data’s usefulness is wasted, leading to sub-optimal business performance.
Our expertise includes analysing data using machine learning and AI techniques in order to better define how it can be made useful and useable. Other services include defining and implementing data science methods for specific business tasks (providing all necessary training), developing specific algorithms and techniques to solve defined data analysis challenges and implementing data mining solutions that enable efficient data analytics.
Unlock the Value of Information Stored in Documents
Around 80% of a typical company’s information is stored in an unstructured way across a variety of documents, presentations, emails, chat conversations and the like. With many companies now suffering from information overload, finding useful and task-orientated information from the huge amounts of language exchanges and records is often an overwhelming task. No surprise then that, even by conservative estimates, employees waste at least 25% of their time simply trying to locate specific information.
Our expertise in natural language processing has the power to change this, by offering:
• Text mining and natural language processing to extract information from unstructured sources, transforming it into structured information that computers are able to deal with, so that humans can use the information more efficiently too. One example here might be automatically categorising documents by subject matter, which means that they can more easily be found in abstract searches.
• Using advanced semantic search and question answering (QA) techniques to provide users with accurate, precise and succinct answers to their queries and questions. This is a significant improvement on merely providing users with a large number of links or documents, where they then have to face the task of locating a specific answer or piece of information.
• Using recommendation systems to help users by proactively suggesting information that might be useful as and when tasks are being undertaken.