Combined Intelligence specialises in the application of Intelligent Technologies, covering the many types and applications of artificial intelligence and also related technologies such as robotic process automation, analytics, intelligent devices and more. Below we introduce some of these key technologies.
Our research and innovation function also ensures we keep track of emerging technologies so that we can quickly identify how they can be incorporated into our portfolio for client benefit.
Please get in touch if you want to understand more.
Artificial Intelligence covers a broad set of capabilities aligned across 4 main intelligence pillars:
- Learning – Machine Learning (and Deep Learning)
- Understanding – Expert Systems, Knowledge bases, Rules engines and Graphs
- Reasoning – Planning, Scheduling and Optimisation
- Communication – Natural Language Processing, Speech, Vision, Hearing
For each field there are various approaches, for example in machine learning there is supervised learning, unsupervised learning and reinforcement learning. Each approach has many options in terms of how data is prepared, used and then how the best algorithms and models are selected. There are also many different platforms, tools and frameworks to support AI development and deployment. These range from open source Python based libraries through to full cloud MLOps platforms from organisations such as Microsoft, Google and Amazon.
On top of these base AI capabilities vendors are building an increasing array of AI applications, ranging from chatbots through to autonomous vehicles. AI is also being utilised with other technologies such as Robotic Process Automation, Intelligent Devices and Analytics (see below) to enhance what they can do.
The world of AI is large, complex and continues to expand rapidly. This makes it difficult for organisations to identify how AI can be used to deliver significant benefit for them, let alone understanding what form of AI to chose and which particular applications of AI will deliver the greatest return. Even when an opportunity has been identified, both the actual implementation and the promotion of AI to live use are a significant challenge. Many organisations have struggled to transition from an inital promising prototype to a robust production quality deployment. Aspects such as bias, ethics, explainability, security, availability, resilience and operational change need to be factored in.
At Combined Intelligence, we’re built a team with extensive knowledge of AI and it’s practical application. We augment this with specialist associates and partners to ensure we have the skills and knowledge across the breadth of AI. We invest significant time in tracking the progress of AI and the evolution of solutions available from the many AI platform and application vendors. We also work with universities and research organisations to understand the future of AI and how these advances can be factored into our clients long term strategy.
Combined Intelligence is here to help our clients realise the benefits of artificial intelligence now and also for the future as the technology continues to evolve rapidly.
Automating parts or all of a business process provides a significant opportunity to:
- Transform process and business efficiency
- Improve accuracy and raise quality
- Enhance the end customer and the employee experience
- Be more responsive
- Eliminate dull repetitive tasks
- Reduce costs
- Improve Management and Business Intelligence
Automation can actually be achieved through a range of technologies, although the most high profile approach at the moment is the application of Robotic Process Automation (RPA).
At Combined Intelligence we believe RPA needs to be applied intelligently as part of a digital transformation strategy and with consideration of how other technologies combined with process reengineering can deliver the maximum benefit. Automating ‘as is’ processes with RPA may deliver short term benefits but it can cause long term challenges with reliability and maintainability as well as limiting the full potential of automation.
Intelligent Process Automation and Hyper-automation are terms being used for the next phase of RPA which combines RPA with AI and other technologies to enhance the levels of automation that can be achieved. RPA is typically rules based, the application of AI enables more intelligent processing of data and decision making, broadening the levels of automation that can be achieved.
Vendor selection can also be a challenge as there are now multiple (20+) different RPA platform vendors, although there remains a big three of Automation Anywhere, Blue Prism and UiPath.
The broadening of functionality within these RPA platforms combined with the addition of RPA functionality into other enterprise applications and platforms is increasing competition. Customer service platforms and low code platforms such as those from Pegasystems, Appian and Antworks are alternative platforms worth considering. Ultimately, it’s important to consider an organisations overall vision and goals when selecting an automation platform as it will rapidly become a business critical platform.
We have the knowledge and experience to help you select an automation platform, to optimise the use of this platform and also to transition process automation into intelligent process automation and hyper-automation. We also recognise that many organisations may have had some initial successes with RPA but have struggled, for various reasons, to scale this out to the levels the organisation wants. The Combined Intelligence team has the experience to help you make this transition.
Read more about Automation and how Combined Intelligence can help you be successful on your journey to Hyper-automation.
There are four types of analytics:
- Descriptive – To describe or summarise existing data using traditional business intelligence tools to better understand what is going on or has happened in the past.
- Diagnostic – Looks at past performance to determine what has happened and why. The result is often presented via a dashboard including visualisations.
- Predictive – Seeks to predict what will happen next or in the future.
- Prescriptive or Preemptive – A type of predictive analytics that is used to recommend a course of action based on predictions.
Using techniques such as data aggregation, data discovery, data mining and correlation, traditional analytics tools have been used extensively to support descriptive and diagnostic analytics. Statistical models also enable the generation of predictions and forecasts. The introduction of machine learning into analytics has enhanced all these types of analytics by, for example, being able to find new patterns within data, generating more detailed and accurate predictions and producing recommendations for the next course of action (prescriptive analytics).
Augmented Analytics is a relatively new term that is now being used to describe the coming together of analytics with AI and automation. Adding automation enhances the efficiency of collecting and analysing data and also improves how the actionable insight generated from the analysis is made available and used within automated business processes.
Combined Intelligence has the knowledge and experience across the fields of analytics, AI and automation to help you achieve the full benefit of Augmented Analytics.
Many devices are now gaining intelligence whether directly within the device via new AI components, via connected devices (such as SmartPhones) or supported through edge or cloud based connectivity. The continuous evolution of connectivity, such as the rollout of 5G, is increasing the bandwidth available to connected devices and also reducing connection latency. This combination is enabling new opportunities, for example, the application of augmented reality within field operations, manufacturing, healthcare etc.
Smart Devices, e.g. Alexa, Siri, Hey Google enabled, are providing new ways of interacting with people. The Internet of Things is meaning devices such as fridges, heating, doorbells etc are gaining connectivity and enabling new intelligent functionality. Connected cameras, sensors and other devices are enabling the creation of Smart Cities.
Fully autonomous vehicles will become reality soon and how long will it be before they fly! Drones are being used for many applications and the world of robotics continues to evolve proving increasingly humanlike capabilities.
These intelligent devices are providing new and evolving ways to:
- Interact with customers and the wider world
- Provide new products and services
- Enhance and optimise processes
- Work more efficiently
- Gather useful data
- Gain insight
Utilising these new devices and associated enhanced capabilities will be key to organisations ongoing success and market differentiation. Combined Intelligence can help you factor these into your business strategy and future operations.
Big Data & Cloud
For many companies, the explosion of data being generated by their organisation has become challenging in relation to how it is stored, how it is analysed and ultimately in how the value that can be extracted from it can be maximised. It is therefore very important to have a data strategy that:
- Allows for the ever expanding universe of data collected
- Supports the migration from siloed data stores to big data platforms and cloud storage
- Enables data to be readily but securely accessed by management information systems, reporting and advanced analytics tools
- Provides for data to be available in bulk for machine learning but also for real time use in automations
We find some enterprises use their complex data strategy and data quality challenges as a reason to delay the adoption of advanced automation and analytics. But we often find that accelerating the adoption of such intelligence technologies can actually help and support your overall data strategy and transformation programmes. We also see a focus on the migration to cloud as a key strategy to help support a remote workforce. With some firms implementing a multi-cloud solution for increased resilience and recovery.
Our team has exceptional experience in managing such programmes and can help with the strategy and implementation to increase your organisations data analytics capabilities while accelerating your big data and cloud migrations.
Technologies such as blockchain which have been around for awhile and have become popular for certain applications, i.e. cryptocurrency, are still considered an emerging technology for other applications.
While technologies like quantum computing might seem futuristic and unlikely to benefit your organisation, the application and benefits of these types of emergent technologies are only just starting to be understood. For example, we know that quantum computing can dramatically reduce the computational time for highly complex problems, some of which are beyond the scope of conventional computing techniques, opening up new business opportunities.
Combined Intelligence has a research and innovation function that continuously seeks to understand emergent technologies and how they should be factored into our clients vision and strategy.