XenonStack Recommends

Cognitive Automation

Use Cases for Continuous Intelligence for Businesses

Dr. Jagreet Kaur Gill | 15 May 2023

What is Continuous Intelligence?

Continuous Intelligence (CI) is the way for systems to know what is happening around them in real-time, so they act accordingly, google maps in our case. It is around us, and we deal with it daily in some way or another. It has become the most crucial part of our daily life.

Suppose Your best friend is in need when you get stuck or lost in any corner of the globe and crave the right direction. Google Maps has come to the rescue, and it is using its platform behind the scenes to track your location at each point in time alongside the details of traffic en route. This innovation insight for it will discuss its types, role, benefits, and more. Stay tuned!

Continuous intelligence is a design pattern in which real-time analytics are integrated into business operations, processing current and historical data. Source:  Gartner

What are the Various Types of CI Systems?

Basically, there are two types of Continuous Intelligence systems:
  • Proactive Push Systems: These are always in listening mode and wait for any opportunity to occur to push responses automatically.
  • On-Demand Systems: The user has to invoke the system. On invocation, it starts processing and triggers a response after reaching a decision.

Role of Continuous Intelligence in Present Scenario

It enables the Artificial Intelligence approach, reducing the burden or eliminating human intervention on many tasks. IT professionals are always surrounded by massive amounts of notifications and logs from system and monitoring tools. Thus some may get ignored and can lead to response delay for about weeks or even months. With its platform enabled, this reduces alert fatigue and quick response as the CI tool identifies the logs and alerts and comes up with a solution or approach to fix. IT professionals are provided with it on the go, and they need not manually identify or study each log or alert. This eventually leads to a faster response. Cloud platforms and application containers are rapidly deploying software and hardware and halting traditional tools and processes.

Continuous Intelligence enables businesses to make decisions while events are happening. Taken From Article, Real Time Analytics with CI

 What are the Use Cases of Continuous Intelligence?

A report points towards by the end of 2023, more than half of the new businesses will introduce it in their work environment. So how can its platform be beneficial for an organization?

Reducing the workload of your IT team

IT teams receive tons of notifications from various alerts and monitors being set up. Most of them are complex and take time to understand what it is about. Others take time to solve as IT teams need time to find the right approach to a particular alert. With the introduction of the Continuous Intelligence platform, issues can be tracked down even before they occur as CI tools intelligently reduce data patterns. It can also give them the right approach to solve a particular alert by deducing patterns from the alert data.

Supply Chain Management

If supply chain analytics are controlled according to the circumstances, they will be far more valuable. Real-time decisions that follow the market can be driven by fusing the most recent sales, economic, and seasonal data with inventory, transportation, and other supply-side factors.

Value-Driven Healthcare

A CI application that rapidly compares risk-associated factors to a patient's medical history and conditions, personalizing complex diagnostics, and directing value-based actions like early intervention, might be powered by combining personal health and medical conditions data.

Cyber Security

A cybersecurity threat may go unnoticed by a team member (genuine human error). Still, if the CI tool is implemented in the system, which is AI-driven capability, it can raise alert to the team and, more specific to the human response. This can save an organization from chaos. Know about The Role of Artificial Intelligence in Cyber Security here.

Analytics for Operational Monitoring

Operations can be optimized in various ways by using real-time contextual data and analytics enabled by AI/ML. With alerts and prompted actions across lines of business, track performance, foresee risks and opportunities, and proactively address business events.

IoT-Based Predictive Maintenance

Manufacturing, utilities, and other industries benefit from 5G technologies and IoT data-powered Continuous Intelligence. AI/ML processing and historical & real-time data can predict and implement required maintenance, maximizing efficiency and business continuity.

Preparation for Emergencies for Logistics

By definition, emergencies constitute real-time, dynamic events. Both government and private sector institutions may predict and adjust personnel, equipment, and processes as emergencies arise by combining operational data with current weather and disaster information.

Monitoring and Reduction of Fraud

A CI-driven strategy is necessary to address the increase in illegal financial activities. Continuous intelligence significantly impacts the market by monitoring ongoing transactions to detect irregularities, notify employees, or block transactions as they happen.

Efficiently integrate analytics to gain insights to make more accurate predictions. Real-Time Analytics Strategy for Enterprises

Continuous Intelligence in Highly Regulated Industries

Organizations in regulated industries integrate CI into several aspects of their operations. A clear challenge in such an industry is gaining access to personalized data, the use of which is regulated by privacy regulations. Such applications often require special processes to access this data. Additionally, additional measures should be taken to ensure that data remains protected throughout its use in CI analytics workflows.
Organizations addressing these issues can apply predictive analytics and AI to their data to gain real-time insights that can be used for immediate action. Examples of CI in regulated industries include:


Using predictive analytics, organizations can provide personalized, real-time advice to patients based on an individual's health and history.

Government/Public Sector 

By using CI on a collective set of data, the project allows the state to predict demand and deploy assets appropriately. For example, if heavy snowfall is forecast in an area and there are not enough snow plows to support the load, neighboring counties with less rainfall may require to make additional snow plows.


CI is implemented in a variety of ways, including automated systems that use AI to detect suspicious transactions in progress. ICs are also used in robotic processing automation (RPA) solutions that mimic user actions to perform large and repetitive tasks, allowing users to focus on tasks with higher value.

What are the benefits of Continuous Intelligence?

Following are the benefits enterprises are leveraging with CI

Analytics in Real Time

Automatically discover patterns in historical data to detect trends in new data that differ from expectations. Information is ranked by relevance and is proactively provided to users as comprehensive data stories with full context.

For example, service personnel can identify hot topics of interest through continuous intelligence, as indicated by an unusually high number of open requests. They can then respond with the appropriate document for more information.

Discover the Unknown with Artificial Intelligence

Complementing analytics that provides exact answers to questions users know to ask, the machine continuously monitors the data in the background to find unknown correlations that differ from what the system expected based on previous observations. You can detect relationships and trends.

  • Increase efficiency by reducing the time shifting through data from disparate sources
  • Focus on what really matters to the business
  • Shorten time to action

By automatically examining business-critical metrics such as revenue, websites viewed, active users, or transaction volume in real-time, businesses can shorten analysis time, act & react better to situations before an activity is affected.

Move at the Speed of Market

Relying solely on failure indicators and following standard KPIs is no longer enough to understand and respond to the dynamics of complex systems or companies.

In the future, intelligence is constantly set to become the norm, as the speed at which businesses must react to rapidly changing market conditions will only increase. It will be essential for companies that want to direct users to relevant data and trigger actions when it matters most.

CI enables us to make smarter business decisions using real-time data streams and advanced analytics. Click to explore about our, Continuous Intelligence in DataOps

How is Continuous Intelligence related to Big Data?

The original vision of Big Data is to collect different sorts of data from various sources and move to a single place where further processing would be done. However, these data were sometimes incompatible with the existing BI tools, and therefore a stage needed to be added to the pipeline known as Data wrangling. Know what is big data here with us. Data Wrangling, aka Data munging, converts data from one form (raw) to another, i.e., compatible with tools. This slowed down the decision-making process. With the introduction of AI-driven platforms, automating the data processing job has become relatively easy. One can use a Continuous Intelligence platform such as ‘Spark.’ With just one click, it can extract and normalize data from various sources and automatically send visual insights to organizations.

Continuous Intelligence vs Business Intelligence

Simply put, Business Intelligence is that kid from high school that requires a teacher’s guidance on every step involved in chemistry practicals. He is the one who grasps things quickly and needs to be taught once. After that, he can do the full practice on his own. Business Intelligence mostly depends on the skills and expertise of individuals running the BI tool, and they have to perform each of the following steps manually.

  • Data Pulling
  • Integration
  • Interpretation

Artificial Intelligence and Machine Learning back Continuous Intelligence. Also, proper training does all the processes independently, intelligently extracting quality patterns from the data and giving end users a continuous flow of high-quality information no matter how complex the data is.


Our brains' hidden Continuous Intelligence can conclude that CI is precious to businesses from the above information. With the integration of Artificial Intelligence, it can provide various benefits to a company. The free flow data and AI-powered CI platform will provide an organization the benefit of intelligently produced high-quality data. It’s going to boost the workflow environment, thus leading to more profit and better results.