Mindbreeze Recognized in the 2021 Gartner ‘Critical Capabilities for Insight Engines’ Report

Mindbreeze was named in the Gartner ‘Critical Capabilities for Insight Engines’ report. In this report, analysts Stephen Emmott and Anthony Mullen evaluated 15 vendors in the Insight Engine space. They were evaluated and given ratings in various areas of performance, as well as given a thoughtful write-up regarding the overall product offering. Mindbreeze was ranked highest in the Internal (Intranet), Extraction of Data for Analytics and Automation, and Insight Applications Use Cases. Here we will discuss what this means for Mindbreeze and our thoughts about a few of their predictions.

Daniel Fallmann, CEO, and the entire team at Mindbreeze were humbled and honored to be ranked in the Gartner report. As a company, everyone works very hard to deliver the highest quality, and it was terrific to be recognized by one of the world’s leading analyst firms. We were evaluated on intranet search Use Cases, extraction of data for analytics and automation Use Cases, extraction of data for analytics and automation Use Cases, and insight applications Use Cases. If you would like to learn more, you can download the report here.

The Gartner report says the following about Insight Engines:

“Insight engines provide a range of capabilities to extract and contextualize data in support of digital dexterity and automation. Applications and software engineering leaders should view insight engines as a key component of the digital workplace and hyperautomation.”

Interestingly, Gartner also makes a few future predictions about this industry:

• By 2023, 60% of organizations will seek composability in new application investments.
• By 2023, 85% of AI solutions by vendors will focus on concrete domains and industry verticals.
• By 2025, 80% of large enterprises will need to have a conversational-technology-focused center of excellence or skills resource.””

Our Thoughts on Gartner Predictions:

The Gartner predictions, in our opinion, are spot on. Now more than ever, organizations need to work together to manage the complexity and velocity of data in these digital times. Data science techniques help companies uncover opportunities and build predictive models that deliver value faster and with greater precision. Insight engines transform data into actionable insights and enable machine learning solutions that provide the digital workforce with insights they need to make smarter decisions faster.

Global competition for talent, talent skills, and talent preferences coupled with weaker business engagement has propelled AI investment among technology companies moving forward. In an era of digitization, choices about information source and lifecycle management are informed more than ever by actionable business intelligence insights. With its rising importance, more data is essential for automated decision-making.

In recent years, Big Data has experienced radical transformations as enterprises look for new ways to manage large amounts of unstructured data in an efficient and cost-efficient manner to fluctuate between business needs and priorities. Toward the end of any crisis, similar to what we have experienced with the Pandemic, many companies realize not all information is usable. That's where digital integration, integration, and automation comes in handy. Prior to their ability to process vast amounts of data as business intelligence systems, data analytics mainly depended on manual data cleansing processes and complex, in-house algorithms. Because of agile development practices and software automation, data analytics, and digital transformation have advanced significantly. Also, with the adoption of Big Data, machine learning can give companies the power to discover patterns and create hypotheses to solve complex business problems.

Thanks to organizations' continuous digitization efforts, business intelligence systems, with the help of analytical tools, can quickly and seamlessly process large amounts of data and turn it into data sets that allow AI and statistical techniques to conduct powerful predictive and prescriptive analyses. That provides businesses with a viable route to transform their current existing data structures, boost business sensemaking capabilities and accelerate upskilling. The huge opportunity inside every company is to capture and access data at scale to help drive innovation. To do so, businesses need the tools to create and understand insights, and that is the role of Insight Engines today.

Gartner, ‘Critical Capabilities for Insight Engines’, Anthony Mullen, Stephen Emmott, March 30, 2021

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