Being named this month as a Visionary in the 2021 Gartner Magic Quadrant for Insight Engines feels like a significant reward. Not just for our team, whose talent and commitment have enabled some of the world’s biggest companies to turn their data into valuable, actionable insights, but for our customers too. This is the first time that we have been named in the Magic Quadrant, but our customers have been believing in us for years.
Gartner defines Visionaries as “combining their understanding of the insight engine market with strength in innovation.” It says that they are “suitable for organizations looking to modernize and transform themselves by tackling familiar problems in new ways.” We couldn’t agree more. The best relationships we have are with companies that are curious about how artificial intelligence can be put to work to gather data, search intelligently, deliver analysis and support data visualization. These are not just our customers, but partners too.
Transformation Through Insights
Organizations today can be so overwhelmed by data that it’s hard for them to know how to access or use it. Activating it can mean committing to major infrastructure upgrades or implementing cultural changes that will allow them to move out of siloed ways of working. Making that decision is not easy, but for those that can see the huge benefits of modernization, an untapped world of data is waiting to transform their business.
Based on our analysis of the report, Gartner acknowledges the impact that insight engine implementation can have and advises, in the Context section of the Magic Quadrant, that “they should never be treated as discrete, insular applications. Rather, they tap into, enhance, and extend a wide variety of other data types, sources and systems.”
Per our understanding, the report points out that insight engines are “integral to an organization’s digital ecosystem, which is complex, extensive and interconnected.” At Squirro we recognize this, and we have worked hard to make the onboarding process as frictionless as possible by creating tools that can be easily integrated by enterprises with any data source via pre-existing connectors. Our solutions are fast to deploy and can be used independently or integrated with enterprise software. We deliver out-of-the-box apps and we have built-in an automatically generated 360˚ client cockpit that helps to improve decision-making. In other words, we have made it as easy as possible to use our insight engine.
Based on our understanding of the report, one key trend that was highlighted by Gartner in its Market Overview was natural language and conversational interfaces. The analyst company has seen “an evolution in the AI techniques and modalities supported by insight engines, which now often offer a broader range of natural language-related technologies such as conversational AI.”
This is something we have been incorporating into our own solutions, using natural language to fit more conversational searches. We have found that connecting various data sources, internal and external, and analyzing the contents with NLP derives considerable value, particularly among our banking and finance customers. Find out more about how Standard Chartered Bank in Singapore is using NLP within our Augmented Banking Application here.
Looking towards the future, Gartner says that “as businesses evolve to become digital and to generate more structured and unstructured content, the need for insight engine technology to surface relevant facts, content and knowledge to stakeholders is critical.” This is true, but the key to optimizing the technology is ensuring it can be used by data scientists, business analysts, data analysts and machine learning engineers. It is these users that will shape the landscape for multiple different sectors from banking and insurance to IT services and healthcare.
To that end, we have developed our new solution, AI Studio. This allows those analysts, engineers and scientists to rapidly develop artificial intelligence and ML models through a user-friendly and visual interface. It is also structured in four steps, so it can support the full AI lifecycle.
Like so many other companies, we have experienced a year of tumultuous change, but we have made significant progress and for us, being named among respected peers in the Magic Quadrant is the icing on the cake. We won’t rest on our laurels, however, because when it comes to insight engines and the need to extract maximum value from data, there is still a lot of work to do.
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