Blog - Virtualitics

The Department of Defense is tasked with the immense responsibility of protecting the United States and its interests at home and abroad. In an era marked by complex threats, rapid technological advancements, and global challenges, the DoD’s role is more critical than ever. To fulfill this mission effectively, the DoD must rely on proven technology that delivers data-driven insights.Virtualitics specializes in using AI and Intelligent Exploration to visualize complex datasets and identify actionable insights. We hit the road over the last few weeks to take our solutions to federal events across the United States.

AI as the Ultimate Assistant

At the 2nd annual AI for Contested Space Workshop in Colorado Springs Kyle Rice, Virtualitics Federal CTO, spoke about “Leveraging AI for Better Decision Making Across the Space Enterprise.” This conference was focused heavily on how AI can assist the specialists who are modeling space effects and autonomous space operations. Virtualitics sits on top of the data that AI researchers like these produce, and make the results accessible to leaders throughout the force.

Kyle’s next stop was the AFCEA Mid-America Cyberspace Conference, where he spoke about using AI to enhance defense cyber operations. The focus of this conference was on the pre-validation of models—meaning how to determine what is important for a cyber team to model before they invest the time and resources to create that model.

In both cases, Virtualitics offers the ability to use AI to assist in understanding data deeply and quickly, finding connections across incredibly complex datasets. By finding safe and strategic ways to add AI to their toolbox, leaders can discover the insight that will save time and empower them to make the right decisions.

Virtualitics also participated in the annual AFA Air, Space, & Cyber Conference. Eugénie Hagemann, Virtualitics Business Development Executive, was a member of our team and shares her experience:

“It was great representing Virtualitics at this year’s ASC conference and meeting with customers from the USAF and USSF. AI is certainly a hot “buzzword” not just at this conference but across the public sector in general. I felt it was important to be able to showcase exactly how Virtualitics is leveraging AI in our Intelligent Exploration Platform to guide users through their data and create visualizations that communicate findings effectively and efficiently. This message resonated with the audience and we had many great conversations at our booth around utilizing IEP across problem areas such as Resource Optimization, Cyber Analysis, ISR, and Program Assessment.”

AI Brings Real Solutions for Mission Readiness

These events provide opportunities for Virtualitics to share our expertise and demonstrate innovative solutions. We also believe strongly in contributing to the collective knowledge of the DoD community and fostering collaboration. By connecting with DoD users at these events we better understand their specific needs and continue to build lasting relationships. Early collaborations can lead to tailored solutions that address the unique challenges faced by the DoD, such as Integrated Resource Optimization and Cyber Analysis, that help DoD teams meet their goals and objectives.

Virtualitics recognizes that by assisting the DoD in achieving its mission, we are contributing to the success of national security and the safety of our country. Learn more about Virtualitics and the solutions we provide for Federal customers.

Unstructured data is produced in abundance by every business in some way. Whether it’s images and videos, text-heavy emails, or sensor data, all of these have the potential to increase competitive advantage if meaningful, actionable insights can be extracted from them. But traditional analytics tools haven’t been optimized to pull from or make sense of unstructured data sources. This means organizations are excluding a huge cache of their data from all their analyses—and potentially leaving revenue-generating information on the table. Fortunately, advances in AI technology now enable businesses to leverage their unstructured data in exciting new ways.

The question is, in the world of unstructured data, how can organizations extract key insights from this dataset—without the headache?

What is Unstructured Data?

Unstructured data is anything that doesn’t have a pre-defined data model nor is it organized in a pre-defined way. It can be human- or machine-generated and usually doesn’t live in file-based systems rather than transactional ones.

Examples of unstructured data include:

Analytics from AI and machine learning algorithms
Sensor data
Functional data from Internet of Things devices
Geospatial data
Weather data
Surveillance data
Collaboration and productivity applications
Text files (e.g., emails, spreadsheets, chatbots, scholarly journal entries)

Many of today’s data management challenges stem from the fact that up to 90% of the world’s data is unstructured, and that number is only going up. According to some predictions, the amount of unstructured data will increase to 175 billion zettabytes by 2025.

The Difference Between Unstructured Data and Structured Data

While unstructured data is heavily prevalent within organizations, there is an abundance of structured data as well. Structured data are records in a database environment that can be easily mapped into designated fields (like name and zip codes) and have clearly defined data attributes. Because of this, they are easy to search and pull information from.

On the other hand, unstructured data comes in so many different formats that it’s been difficult for a single data mining tool to be able to process, search, and analyze these. But there is a massive amount of information and insight to be found in unstructured data if you have the tools to understand it.

What are the Advantages of Analyzing Unstructured Data?

Nearly everything we do—from collaborating with coworkers to shipping inventory to heating and cooling our offices—is enabled and improved through the analysis of unstructured data. The main benefit of analyzing this type of dataset is that it provides businesses with the whole picture of the organization so they can see exactly where opportunities, and threats, lie.

For example, targeted marketing strategies can be improved by analyzing consumer behavior trends, call center transcripts, online product reviews, chatbot conversations, and social media mentions. Analyzing all this multidimensional data for patterns can reveal intel that better personalizes the customer web experience or determines the best time to send out email offers that lead to improved sales.

However, surfacing these insights isn’t a simple process.

Why is Unstructured Data Challenging to Use?

The lack of consistent structure makes this data incredibly challenging for traditional BI and analytics tools to ingest and analyze. There are two main issues with unstructured data that need to be overcome to maximize its value: expense and complexity.

1. Expense

The massive quantity of unstructured data can significantly increase costs for cloud-based storage. To keep storage expenses in check, it’s helpful to evaluate all of your organization’s data and create separate storage strategies for cold and hot data.

The unchanging or “cold” data can be stored in unmanaged cloud-based storage, freeing up your budget for storing the “hot” data that requires regular backup and replication.

Legacy data management systems are another potential source of extra spend. Legacy systems often do not play well with modern unstructured data management solutions, which may require custom-building a solution to effectively process and manage high volumes of unstructured data.

2. Complexity

Unstructured data also introduces additional complexity to enterprise data analytics. With a large amount of raw, unorganized data flowing in from many disparate sources, indexing is difficult and error-prone due to unclear structure and lack of predefined attributes.

This disorganization and lack of well-defined attributes makes it difficult for analysts to determine which datasets are relevant to a particular use case and whether the data is high-quality and trustworthy.

The Virtualitics Intelligent Exploration platform collects all kinds of unstructured data, then uses AI-based data analytics and multidimensional visualizations to surface insights that empower analysts to bring revenue-generating ideas to stakeholders. With Virtualitics, organizations in every industry can take control of their complex data management and put their unstructured data to work.

Make Sense of Unstructured Data with Intelligent Exploration

The amount of unstructured—and structured—data that your organization produces will only continue to grow. Artificial intelligence and machine learning analytics software is the key to understanding the patterns, relationships, and trends hidden with all your complex, multidimensional data.

Virtualitics not only uses AI to power our industry-leading analytics and visualization tools, but also provides guided and automatic insights that help analysts and other non-data scientists read, understand, and use the data independently. With everyone in the organization benefiting from the power of AI-driven analysis, you’ll be able to maximize the value of every piece of business data produced.

Approximately 2.5 quintillion bytes of data are produced every day (for reference, there are 18 zeros in that number!). Companies contribute an immense amount of data to those bytes and for a long time, BI dashboards were enough to make sense of all that information. But as datasets continue to grow and become more complex, the limitations of BI tools are leading to a mind-numbing phenomenon known as “Death by Dashboard.”

Similar to the “Death by PowerPoint” meetings featuring decks with 100+ slides, BI dashboards are being packed with reports and data points until they resemble an abstract painting more than a tool for deriving valuable business insights. There’s simply too much information in them to be helpful or digestible.

Teams who are using overpopulated dashboards are failing to deliver on the value within their treasure trove of data. But the answer isn’t to put less information in your dashboard either because this won’t give you an accurate picture of your business. Instead, to gain strategic business insights, you need advanced and AI-guided analytics tools that allow for deeper exploration of your data.

5 Reasons Dashboards Fail at Advanced Data Analytics

BI dashboards organize and present data through charts, graphs, and pivot tables. But, according to a CIO report, dashboards “are designed to provide superficial information—not to explore complex problems and unearth the deep insights organizations critically need.”

When dashboards are stuffed with tables and charts in an effort to make them work for advanced data analytics, such as predictive and prescriptive analytics, they result in five main problems for users:

Cognitive OverloadCognitive overload in design happens when the brain has too many choices, there’s visual clutter, or there’s a lack of clarity between the information presented. Too much information overwhelms the brain’s capacity to process it effectively. As a result, individuals may find it challenging to concentrate, make decisions, or retain important details.
Reduced Focus and AttentionExcessive exposure to information can lead to a shortened attention span, which is often what leads us to endlessly scroll on social media. There’s just so much to look at and consume that we become easily distracted or are constantly seeking new information, making it difficult to stay focused on a specific task or topic.
Increased Stress and AnxietyInformation overload can also trigger feelings of stress and anxiety. When presented with a data-packed dashboard, there’s a heightened sense of worry that you might miss something or read a report incorrectly.
Decision Paralysis Overloaded dashboards often end up doing the opposite of what they were intended, which is to help people make better business decisions. In fact, the abundance of information may result in analysis paralysis due to the fear of making the wrong choice, leading to procrastination or avoidance.
Inaccurate or Misleading InformationOverexposure to information makes it difficult to distinguish accurate and reliable sources from misinformation and propaganda. This can lead to the spread of false beliefs or the reinforcement of existing biases.

These five problems are all part of an inherent problem in BI tools—they rely heavily on the user’s ability to manually identify insights. But valuable answers and opportunities get buried when there’s an extremely busy dashboard for a person to wade through. BI dashboards, which often contain static information about the past and can’t identify patterns and relationships in your data, simply weren’t made for data exploration.

Get Answers Without Overwhelm Using AI-Driven Analytics

Getting the maximum use out of your data is critical to success. The Virtualitics AI Platform enables teams to use Intelligent Exploration as they are guided by AI to explore data more in-depth and automatically find insights.

We don’t believe in dashboards with excessive information that overwhelm data analysts. Virtualitics significantly enhances the decision-making process by leveraging machine learning and artificial intelligence algorithms to guide analysts through complex data, highlighting and explaining patterns, predicting outcomes, and providing proactive recommendations.

With the right data analytics tool, your analysts will be empowered with information—instead of inundated by it—that helps them find the strategic answers your organization needs to succeed.

Are you ready to level up your data analysts? Check out our free e-book: Intelligent Exploration for Data Analysts – How Advanced Analytics Tools Turn Data Analysts into Strategic Heroes.

Highlights momentum in emerging data analytics technologies and underscores foundational elements of intelligent exploration.

Pasadena, Calif., Sept. 7, 2023 – Virtualitics Inc., an artificial intelligence and data exploration company, today announced it has been recognized in eight Gartner® Hype Cycle™ reports. Gartner Hype Cycle reports provide a picture of the maturity and adoption of technologies across different functions, and how they are potentially relevant to solving real-world business problems and exploiting new opportunities. In the 2023 Gartner Hype Cycle, Virtualitics is recognized in eight reports, including:

Hype Cycle for Data and Analytics Programs and Practices
Hype Cycle for Analytics and Business Intelligence
Hype Cycle for the Future of Enterprise Applications
Hype Cycle for Data Science and Machine Learning
Hype Cycle for Emerging Technologies
Hype Cycle for Emerging Technologies in Finance
Hype Cycle for Finance Analytics
Hype Cycle for Human Services in Government

“Gaining recognition across eight Gartner Hype Cycles and in 3 separate categories, including graph analytics and multi experiential analytics, is an exceptional milestone,” said Virtualitics CEO Michael Amori. “We’re especially pleased to be being singled out in the Future of Enterprise Applications category. I see this as an important marker of our leadership in a new category of data analytics we’re creating, Intelligent Exploration.”

Intelligent Exploration uses out-of-the-box AI to bring advanced analytics within reach of business and data analysts, not just data scientists. Users can make queries in everyday language, explore extremely complex datasets, uncover critical insights, and generate multi-dimensional visualizations.

Virtualitics’ AI-driven analytics solution includes innovations at multiple phases of the Gartner Hype Cycle: graph analytics, multi experiential analytics including VR/AR collaboration, explainable AI, natural language query, data storytelling, and augmented analytics (enhanced by AI), among others. Together, these technologies form the foundation for Intelligent Exploration.

In the realm of finance, Intelligent Exploration is being used for customer segmentation and to explore and understand payments intelligence. Credit card issuers can detect and predict fraud risk factors using Virtualitics’ 3D network graph algorithm to visualize subtle, recurring patterns and define communities that humans can’t spot.

The Gartner Hype Cycle news follows Virtualitics’ August announcement of a $37 million Series C investment by Smith Point Capital and inclusion on the Inc. 5000 List of Fastest-Growing Private Companies in America. “If I had to use one word to characterize what we’re achieving and doing, it’s acceleration,” says Amori. “Both in terms of our growth as a company and in how we are accelerating informed strategic decision-making.”

To view a copy of the 2023 Gartner® Hype Cycle™ for Analytics and Business Intelligence visit www.virtualitics.com/hypecycle.

About Virtualitics

Virtualitics is pioneering Intelligent Data Exploration, delivering out-of-the-box artificial intelligence capabilities that make advanced analytics possible for more people and organizations. The Virtualitics AI Platform automatically discovers hidden patterns in complex, multi-dimensional data, delivering rich 3D visuals and immersive experiences that guide more informed decisions. Virtualitics helps public and private sector organizations gain real value from all of their data, accelerating their AI initiatives. The company’s patented technology is based on more than 10 years of research at the California Institute of Technology. For more, visit virtualitics.com.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

Resources

Gartner, Hype Cycle for Analytics and Business Intelligence, Edgar Macari, Peter Krensky, 27 July 2023
Gartner, Hype Cycle for Data and Analytics Programs and Practices, Donna Medeiros, Andrew White, and 1 more, 26 July 2023
Gartner, Hype Cycle for the Future of Enterprise Applications, Patrick Connaughton, Tad Travis, and 3 more, 18 July 2023
Gartner, Hype Cycle for Data Science and Machine Learning, Peter Krensky, 27 July 2023
Gartner, Hype Cycle for Emerging Technologies in Finance, Mark D. McDonald, 11 July 2023
Gartner, Hype Cycle for Finance Analytics, Clement Christensen, 21 July 2023
Gartner, Hype Cycle for Emerging Technologies, Arun Chandrasekaran, Melissa Davis, August 2023
Gartner, Hype Cycle for Human Services in Government, Ben Kaner, August 2023

Organizations today recognize the potential of their data to drive business-changing insight. However, as data sets become more complex and robust, analyzing comprehensively using traditional methods has become difficult.

Multidimensional data is one such data set, capable of helping analysts uncover critical information that leads to better strategic decision-making. But this complex data requires looking beyond two-dimensional structures, so not every company is able to take full advantage of it.

Let’s talk about why multidimensional data is so important to businesses and how your analysts can leverage it more regularly.

What is Multidimensional Data?

Multidimensional data is a data set with many different columns, which are also called features or attributes. The more columns in the data set, the more potential there is to discover hidden insights. A two-dimensional analysis falls flat in this regard because it only lets you look at the data through two attributes.

You could organize these multiple attributes on a chart or other 2D rendering, but the human brain wasn’t built to make sense of this much information in this way. It’s impossible to truly see all the connections and relationships happening between attributes. But when multidimensional data is viewed as a cube on multiple planes, for example, it’s possible to look at far more factors in one image.

Multidimensional data models organize the many attributes in a clearer way, enabling users to dig deeper into probable trends or patterns. You can interrogate queries rather than just submit them, as practiced in relational databases. It’s also a comparatively fast exercise, manipulating the different dimensions and perspectives by attribute.
When a noteworthy insight rises to the surface true 3D illustrates the connections concisely. An enormous quantity of relevant data is arranged and depicted in ways that humans can better grasp.

What Are the Advantages of Multidimensional Data?

In simple terms, lots of dimensions deliver lots of information. As a result, the potential for insight increases. Analyzing multidimensional data is most impactful when it’s examined in the way that our brains process best—in 3D.

“Multidimensional visualizations can show more complex analyses and enable the user to look at them from different angles, facilitating discovery,” Virtualitics co-founder and CTO, Ciro Donalek, said in this article. “This visual approach also adds ‘explainability’ to complex concepts that non-data-scientists, such as product owners and management, need to drive decision-making and meet business objectives.”

An AI-driven analysis platform like Virtualitics, which also models data using 3D visualizations, increases the benefits of working with multidimensional data by allowing users to:

Group similar information. All like information combines into a single dimension. This process keeps things organized and makes it easy to view and compare.
Visualize the output of complex data. When working with this model in a platform, you can visually recognize the outcomes of data analysis.
Identify patterns, trends, outliers, and anomalies. There are no hidden data points in this “cubed” data visualization. You have everything grouped and organized so you can more easily recognize the insights. You can also build interactive reports for these elements.
Examine relationships among data from multiple sources. You can add many layers of source data to build your cube and discover patterns.
Improve collaboration and analysis across geographic locations. By using this model, you can more easily work with users with tools in a shared virtual office. It’s secure and allows people from different locations to work on the data at the same time.
Extract valuable information from unstructured data. Unstructured data can be a pain point in analysis, but it’s no longer an issue with multidimensional data tools.
Add “explainability” for non-data scientist stakeholders. Explaining data in an approachable manner is critical to driving better decision-making across the enterprise. Multidimensional data makes this possible.
Compare the impact of changes to variables on the target data easily. If you want to understand the effect of change on specific data, you can with little strain.
Process data quickly. You’ll gain speed with multidimensional data versus a relational database. The setup may be longer, but in the end, your processing will be faster.
Maintain data efficiently. Because you’re storing data in the same way it’s viewed, maintenance is simple.
Save money. Multidimensional data models perform better and are more cost-effective than relational ones.

Want to fully realize the advantages of multidimensional data at your organization? Then it’s crucial to spread its use beyond the data science team and give every business analyst the power to intelligently explore this type of data set.

How Intelligent Exploration Democratizes Multidimensional Data

As organizations continue to create more data and advanced data science skills become harder to find, companies are investing in tools that will enable analysts to go beyond surface-level analysis of limited attributes.

According to Gartner’s Hype Cycle for Analytics and Business Intelligence 2023 report: “Organizations must be able to deliver the most relevant, contextualized and consumable analytics outputs possible. This requires tapping into the unique intersection of various devices, interaction modalities and analytics capabilities that can augment users’ ability to consume insights.”

Intelligent Exploration through the Virtualitics platform empowers analysts to explore complex data with confidence and deliver actionable insight to stakeholders. When powered by AI, visualizations of multidimensional data explain the output of machine learning models and main drivers in a more intuitive way. They also reveal complex relationships that live at the intersection of many dimensions, showing logical connections and communities within the datasets.

With this ability to see—and visually render—complex relationships in data, analysts can more easily perceive what’s really going on and explain their findings to stakeholders.

What Are Multidimensional Data Uses Cases?

Within a business, there are many reasons to leverage multidimensional data and visualizations to investigate the past, present, and possible futures. Here are four use cases:

Improve Target Marketing

Every marketer wants to personalize communication and offerings to specific customers based on a host of data sets. Those may include demographics, consumer behavior trends, and detailed information about a customer’s past interactions with your brand.

With all these attributes, it can be challenging to see correlations in a static, 2D analysis. With multidimensional data models, you see the complete picture, which can lead you to clearer conclusions about how to better reach your target customers. For example, you may find that the time of day influences how big an order is and therefore, schedule email offers to go out just before that hour.

Increase Uptime Beyond Predictive Maintenance

Predicting when equipment needs maintenance before it breaks or fails is key to minimizing downtime. Maintenance indicators vary widely depending on the complexity of the machinery. A great example of this is predictive maintenance for airplanes. These sophisticated machines require multiple technologies to facilitate their operation and maintenance—and all the data these systems produce can be built into a multidimensional data model for proactive maintenance analysis. We call this method Integrated Resource Optimization.

“The connections between key drivers like failure data and your maintenance and logistics activities like time to repair and inventory optimization are the places where you’re able to implement strategic practices that will positively impact your readiness rate,” wrote Jerami Reyna, a former lead maintenance manager in the United States Air Force and now Solutions Lead at Virtualitics.

Prioritize the Right Risks and Outliers

Predictive maintenance is part of a larger practice called Integrated Resource Optimization, which provides a big-picture view of maintenance operations. Let’s say you operate a wind turbine farm spread across multiple locations. Knowing where to prioritize resources can be incredibly difficult, especially when maintenance operations produce and collect a lot of information: parts inventory lists, staffing plans, procedures, repair times, repair logs, shift planning, and so much more.

But when all that information can be centralized and AI helps to analyze the relationships between all the dimensions, you’re able to surface key insights about where maintenance will be most effective. In the case of the wind farm, the system identified that a wind turbine has an average failure risk of only 38%, but the risk of gearbox failure is 95% and will break in about 10 days. It might seem counterintuitive to focus on a wind turbine with low average risk, but by fixing this one component, we can take proactive measures to ensure the overall production of this wind turbine remains high over the course of its lifespan.

Analyzing Complex Biological Data

Multiomics is another use case for multidimensional data. The data sets are all “omes”—genome, proteome, microbiome, and so on—related to health and disease analysis. As you can see, there are many features of the data, and it’s very complex. In traditional databases, there are limitations for researchers because they can only isolate single data points.

The key is the integration of data, but this is difficult to do—unless you’re doing a multidimensional analysis. Such a configuration allows researchers to understand public health better and discern correlations that fill current gaps in knowledge.

Experience the Power of Multidimensional Data

Leveraging multidimensional data lets you see your business opportunities and weaknesses like never before. When analysts are able to explore this data themselves, using the right tools, they become the frontline in discovering, validating, and socializing the projects that add the most competitive advantage to the business.

Ready to learn more?

Join us for a quick demo of our Intelligent Exploration capabilities and see how Virtualitics helps you explore your multidimensional data.

Pasadena, CA, August 24, 2023 – Virtualitics Inc., an artificial intelligence and data exploration company, was named in Fast Company’s Innovation by Design Awards for 2023 in the Artificial Intelligence category.

The company is honored for its role in enabling organizations to harness the potential of their data through a diverse range of AI algorithms. These algorithms automatically uncover and emphasize relationships within the data, generate immersive 3D visuals to enhance comprehension, and provide clear insights aimed at addressing some of the world’s most significant challenges. The overarching mission of Virtualitics is to equip organizations with the capability to tackle intricate, mission-critical issues, a mission they refer to as Intelligent Exploration.

The Virtualitics AI Platform harnesses the power of AI-generated and AI-guided data exploration to transform how organizations use their data. Traditional data exploration methods are shallow and incomplete, leaving companies with a narrow and biased understanding. Virtualitics gives users the power to go deeper to discover the real meaning in the data.

Using AI and machine learning, data teams can quickly and thoroughly explore all of their data, automatically discovering patterns and meaning. The results of this exploration are displayed in Virtualitics’ patented, rich 3D visuals and VR experience, which are designed to display complex findings clearly. This enables stronger storytelling and enhanced understanding, so teams and stakeholders move forward strategically with a strong foundation that guides smarter business decisions and AI initiatives.

“Being included in Fast Company’s Innovation by Design Awards spotlights our ongoing mission to use AI for groundbreaking advancements in analytics,” said Michael Amori, CEO and co-Founder of Virtualitics. “AI stands on the brink of reshaping corporate data comprehension and exploration and is poised to change how companies understand and explore their data, we’re thrilled to lead the way.”

A stunning example of Intelligent Exploration is the company’s network graphs. Network graphs provide unparalleled insight into complex relationships, but because they’ve traditionally required specialized data science techniques and technologies, and produce underwhelming visuals, most organizations aren’t using them. This means teams miss out on insight into the multifaceted relationships and dependencies that define their business. Virtualitics’ automated, patented technology extracts graphs directly from complex, tabular data without any coding from users. The data is then visualized in a 3D graph that can be rotated and explored, and AI-generated insights that help users see what defines their data communities.

The Innovation by Design Awards, honor the designers and businesses solving the most crucial problems of today and anticipating the pressing issues of tomorrow. The competition, now in its 12th year, features a range of blue-chip companies, emerging startups, and hungry young talents. It is one of the most sought-after design awards in the industry. To see the complete list, go to https://www.fastcompany.com/innovation-by-design/list.

About Virtualitics

Virtualitics, Inc., the Intelligent Exploration company, is pioneering the power of AI- and machine learning-guided data exploration to transform organizations. The Virtualitics AI Platform is an advanced analytics solution empowering everyone with faster, ready-to-use AI that is easily understood by analysts and business leaders. The company’s patented technology is based on more than 10 years of research at the California Institute of Technology and has been tested, proven and leveraged by the federal government and large enterprises. For more information visit virtualitics.com

AI allows a lot of work to be done at scale. Sounds good, right? But when your job is scamming organizations and people online, this translates into a lot of crime—and massive expenses for organizations that are constantly vulnerable.

The cost of cybercrime globally in 2023 is projected to reach $8 trillion. That means that if it were measured as a country, cybercrime would be the world’s third-largest economy after the U.S. and China. That estimate is largely driven by the scale and innovation that AI makes possible in cybercrime.

On the flip side, AI is a vital and potent tool in mitigating cyber risks. Here’s an overview of how AI is both driving explosive growth in cyber attacks and how it helps defend against four of the most prevalent types of attacks.

AI is an engine for cybercrime

AI makes online scamming easier in several ways. It increases cybercriminals’ bandwidth by allowing them to target larger audiences, faster. And it puts tools for malfeasance in more hands.

It no longer takes a lot of resources to get a cybercrime effort up and running. Buyers are purchasing out-of-the-box, whole phishing kits, complete with fake web pages that credibly impersonate companies and step-by-step instructions on how to run an email phishing scam. Untrained hackers can now launch a cybercrime campaign for a few bucks. The FBI is in the midst of prosecuting a darknet user who allegedly created malware using generative AI, then offered instructions to other cybercriminals on how to use it to recreate malware strains.

Creating and countering more personalized, on-brand phishing

Phishing—tricking users into giving up security credentials, organizational data, or financial information—has gone next level with generative AI like ChatGPT. Fraudsters can now create fake emails, texts (smishing), voicemails (vishing), and social media posts without grammatical errors, in a brand’s voice, peppered with personal details gathered from the entire internet—and appealing emojis. Malicious attachments get delivered not just when a user clicks through to sketchy free streaming sites but via services in everyday business use.

The lures are so believable that it’s getting impossible for victims to distinguish scams from genuine communication. This is a real killer for productivity, as staff members spend more and more time just trying to sort scams from what’s authentic.

Until recently, the traditional method of stopping email-delivered threats relied on assessments of previous attacks. But historical data is becoming less useful as a predictor of phishing when the creativity of cybercriminals combines with AI.

Cybersecurity tools that leverage AI learn about threats faster, have fewer false positives, and have superior pattern recognition. Data analysts, information security specialists, and administrators can detect keywords, phrases, grammatical styles, and suspicious links unique to phishing. With AI, cybersecurity teams can:

Intelligently explore wide sets of data for signals, on all an organization’s channels: email, customer service text threads, social media feeds, corporate voicemails.
Assess the behaviors that led victims to fall for a ruse such as analyzing language, types of requests, and other elements that typify attacks.
Detect and display communities and commonalities that exist within the data, like third-party contractors who are most at risk of scams, or trending phishing messages.
Move quickly and seamlessly from finding insights to making recommendations, like how to target employee education to best defend against sophisticated scams.

AI-guided forensic investigations and repairs after data breaches

AI is making the theft of sensitive data faster and easier. The list of vulnerabilities bad actors are probing is long: outdated authentication methods, unpatched software, unwitting phishing targets, lax third-party contractors, misconfigured cloud services, data sent unencrypted, insecurely coded web applications, and intercepted communications. With the average price tag of a data breach running $3.86 million, efficient countermeasures that keep up are a must.

The most time-consuming recovery tasks from these attacks are the cleaning and repair of infected systems and getting to the bottom of what went wrong; the good news is, AI is useful in both of those efforts. For example, machine learning can analyze large amounts of data to identify existing and potential threats, such as malicious files or suspicious network activity. This can reduce the amount of time and effort that security analysts need to spend manually reviewing logs and alerts and point teams to specific countermeasures. AI can also identify instances when sensitive data was transmitted without encryption and suggest encryption protocols to safeguard data during transit.

Countering zero-day attacks with AI

Fraudsters are using large language models (LLM) to find flaws in code and craft zero-day attacks. In one recent example, a bad actor used a ChatGPT prompt “act as if this was a zero-day flaw” and pointed to some code that was vulnerable to the SigRed DNS flaw. AI can reduce the impact of such attacks and minimize the damage by automating responses such as isolating infected systems, blocking malicious traffic, and patching vulnerabilities.

Gartner predicts that by 2025, 45% of organizations worldwide will have experienced attacks on their software supply chains, a three-fold increase from 2021. But AI can also potentially detect software vulnerabilities ahead of zero-day attacks, protecting everything from sensitive health data to digital supply chains, a growing target.

How AI helps prevent ransomware incursions

Though some generative AI systems have protections built in to reduce risk, cybercriminals are using LLM to write code for ransomware. They circumvent the prohibition by breaking the task into discrete parts. AI can help prevent these sorts of attacks by identifying and patching software vulnerabilities, identifying the security training employees need, and implementing security policies. It becomes more difficult for attackers to gain access to systems and networks. Organizations that are victimized can also use AI to develop tools to help identify and remove any malicious code or inputs.

Denying denials of service

One recent epic distributed denial of service (DDoS) attack lasted for 8396 hours, including one sustained attack of 87 hours. It was specifically timed to coincide with the day of the 2022 World Cup Final. We can expect more of such “carpet bomb” attacks, as cybercriminals enlist AI-powered bots to generate massive amounts of traffic, making websites or servers inaccessible. Even the most secure websites can be vulnerable.

On the defense, AI can analyze incoming traffic and deem them safe or unsafe using hundreds of different properties and then blocking those that reflect known attack patterns. AI can even fool the attackers into thinking that their mission has been accomplished when it actually has not, disrupting the attack further. AI can learn from each incident, potentially recognizing future attacks even faster.

Cyber security and AI: the ultimate partners in crime to fight against crime

The cost of fighting cybercrime is expected to exceed $11 trillion this year and hit $20 trillion by 2026, a 150 percent jump from 2022. Cybercriminals will only get faster and better as they use AI to continuously analyze data, craft more convincing bait, get smarter about timing, and evade detection.

To effectively combat their endlessly creative, constantly evolving schemes, organizations can use AI for good. They can seek out and detect previously unseen patterns by intelligently exploring their data. They can find commonalities among billions of data points, improve preventive measures, and speed up responses when an attack does succeed. And they can extrapolate from yesterday’s attacks to determine what tomorrow’s will look like.

Learn more about combating cyber attacks with Virtualitics.

On the latest episode of the Intelligent Exploration Podcast, Jeff Vagg, Chief Data & Analytics Officer at North American Bancard explores the tradeoffs of implementing generative AI in business organizations.

Throughout this discussion we delve into various topics, including the impact of generative AI in the data analytics and business intelligence space, the significance of ethical AI, and the benefits of using visualizations to gain insights during data exploration. Listen in as Jeff shares his perspective.

Tune in to this episode on your favorite podcast platform, including:

Leading intelligent exploration company recognized for out-of-the-box AI solutions that help enterprises understand and take action on complex data

Pasadena, Calif., Aug. 15, 2023 – Virtualitics Inc., an artificial intelligence and data exploration company, has made the Inc. 5000, Inc.’s annual list of the fastest-growing private companies in America. The prestigious ranking provides a data-driven look at the most successful businesses within the economy’s most dynamic segment—its independent, entrepreneurial businesses.

Virtualitics is revolutionizing and shaping the artificial intelligence and data exploration sector with its groundbreaking technology, Intelligent Exploration. Virtualitics’ sophisticated AI-powered solution empowers data analysts, and other business users to make better-informed strategic decisions at an accelerated pace. The technology allows users to make queries in natural language, explore extremely complex datasets, uncover critical insights, and generate multi-dimensional visualizations that bring forward hidden insights and relationships in data.

The Inc. 5000 class of 2023 represents companies that have driven rapid revenue growth while navigating inflationary pressure, the rising costs of capital, and intractable hiring challenges. Among this year’s top 5000 companies, the median three-year revenue growth rate was an astonishing 2,238 percent. In all, this year’s Inc. 5000 companies have added 1,187,266 jobs to the economy over the past three years.

“Running a business has only gotten harder since the end of the COVID-19 pandemic,” said Inc. editor-in-chief Scott Omelianuk. “To make the Inc. 5000—with the fast growth that requires—is truly an accomplishment. Inc. is thrilled to honor the companies that are building our future.”

Virtualitics is positioned to transform data analytics. Traditional data exploration tools, like BI solutions, have limited capabilities in identifying and visualizing intricate data relationships, while open-source solutions require provisioning of scarce technical expertise. In contrast, AI-driven data exploration and 3D visualizations on, Virtualitics’ platform empower business analysts to delve deeper into data, pinpoint patterns, and trends, and make smarter strategic decisions.

For complete results of the Inc. 5000, including company profiles and an interactive database that can be sorted by industry, location, and other criteria, go to . The top 500 companies are featured in the September issue of

About Virtualitics
Virtualitics, Inc., the Intelligent Exploration company, is pioneering the power of AI- and machine learning-guided data exploration to transform organizations. The Virtualitics AI Platform is an advanced analytics solution empowering everyone with faster, ready-to-use AI that is easily understood by analysts and business leaders. The company’s patented technology is based on more than 10 years of research at the California Institute of Technology and has been tested, proven and leveraged by the federal government and large enterprises.

About Inc.
Inc. Business Media is the leading multimedia brand for entrepreneurs. Through its journalism, Inc. aims to inform, educate, and elevate the profile of our community: the risk-takers, the innovators, and the ultra-driven go-getters who are creating our future. Inc.’s award-winning work reaches more than 50 million people across a variety of channels, including events, print, digital, video, podcasts, newsletters, and social media. Its proprietary Inc. 5000 list, produced every year since 1982, analyzes company data to rank the fastest-growing privately held businesses in the United States. The recognition that comes with inclusion on this and other prestigious Inc. lists, such as Female Founders and Power Partners, gives the founders of top businesses the opportunity to engage with an exclusive community of their peers, and credibility that helps them drive sales and recruit talent. For more information, visit www.inc.com.

Smith Point Capital leads investment round to accelerate growth in strategic enterprise markets

PASADENA, Calif., August 10, 2023 – Virtualitics, Inc., an artificial intelligence and data exploration company, today announced that it has raised $37 million in a Series C financing round led by Smith Point Capital, LLC with participation from Citi and advisory clients of The Hillman Company, among other investors.

Virtualitics is revolutionizing and shaping the artificial intelligence and data exploration industry with its groundbreaking technology, Intelligent Exploration. Virtualitics’ sophisticated AI-powered analytical capabilities empower data scientists and business users to make informed strategic decisions at an accelerated pace. The Intelligent Exploration platform’s advanced AI technology allows users to make queries in natural language, explore extremely complex datasets, uncover critical insights, and generate multi-dimensional network graph visualizations. Its patented VR/AR capabilities also enable real-time collaboration across multiple users and locations.

The new investment comes at a time of rapid growth and accelerating momentum for Virtualitics, including significant growth in both its public sector and key commercial segments. Bolstering their momentum over the last 12 months, Virtualitics has successfully acquired seven new customers across the Department of Defense and increased customer acquisition in the Financial Services and CPG markets.

“We knew we wanted a strategic relationship with our lead investor, not merely capital,” said Michael Amori, CEO and co-founder of Virtualitics. “Smith Point’s operational expertise in enterprise software has been – and will continue to be – invaluable as we accelerate growth and innovation. This additional funding and strategic guidance will enable Virtualitics to realize our vision to empower organizations to solve complex, mission-critical problems with artificial intelligence, data exploration and prescriptive business workflows.”

“The advanced AI and machine learning capabilities behind the Intelligent Exploration platform are completely revolutionizing the way organizations leverage their data,” said Keith Block, CEO and co-founder of Smith Point Capital. “Virtualitics enables deeper data access through an intuitive platform, opening up entirely new methods to explore complex datasets. Michael and his team are exactly the kind of visionary leaders building the type of businesses that our firm was set up to invest in and help scale. Virtualitics is on a rapid growth trajectory and Smith Point will accelerate their financial and market success with our operational expertise and rigor.”

This announcement comes on the heels of a number of recent key milestone achievements for Virtualitics, including:

New and expanded partnerships with industry leaders: Data cloud company Snowflake, partnered with Virtualitics to place the power of intelligent exploration into the hands of their joint customers, allowing them to use AI to identify hidden connections in their data and explore insights in immersive, rich 3D visuals directly from Snowflake’s single, integrated platform.
Strategic investment from Citi: In May 2023, Virtualitics announced a strategic investment from the preeminent financial services institution to fund the acceleration of the expansion of its AI platform, adding more out-of-the-box machine learning and data analytics capabilities for exploring and analyzing data for financial services.
Award-winning AI: Virtualitics was named to Fast Company’s World’s Most Innovative Companies list for 2023, alongside other global leaders such as OpenAI and Microsoft, for its world-class AI solutions and for turning data relationships into vivid 3D visuals. Additional honors received by Virtualitics include a 2023 Artificial Intelligence Excellence Award from the Business Intelligence Group, which recognizes the organizations, products and people who bring artificial intelligence to life and apply it to solve real-world problems. Virtualitics was also named one of the best Los Angeles startups to work for on Built In’s 2023 Best Places to Work List and one of three companies named to Gartner’s 2022 Cool Vendor in Analytics and Data Science report.
Patented Technology: Led by Dr. Ciro Donalek, CTO and Co-Founder of Virtualitics, the company has recently achieved two significant patent updates. The first patent covers a proprietary 3D network graph algorithm that derives groundbreaking visualizations from tabular data. The second patent focuses on native 3D data visualization, redefining the way data is perceived and analyzed. With these additions, Virtualitics’ portfolio now boasts five patents, showcasing their leadership in the domains of 3D visualization, virtual collaboration, AI-guided exploration, and network graphs.

With this funding round, Virtualitics will continue to invest in growth and innovation to drive even greater expansion, including direct and ecosystem investments and investments to enhance its AI platform leadership by adding more machine learning and data analytics capabilities as well as self-serve prescriptive workflows to make it easy for customers to analyze and understand complex data and transform their business.

About Virtualitics

About Smith Point Capital

Smith Point Capital was founded by leading enterprise technology operators and investors. The firm has a highly differentiated investment strategy; namely, identifying and collaborating closely with the most innovative enterprise software companies to implement proven, best-in-class revenue growth, innovation and operational strategies to dramatically accelerate financial and market success.