Gartner names IBM a Leader in 2019 Magic Quadrant for Insight Engines
IBM was named a ‘Leader’ in Gartner’s Magic Quadrant for Insight Engines 2019 market research report. Insight Engines are defined by Gartner as “an evolution of search technologies that provide on-demand and proactive knowledge discovery and exploration augmented by semantic and machine learning (ML) technologies.” The Magic Quadrant report –created to assist decision-makers in selecting the right technology provider for their needs –ranks vendors according to two criteria: completeness of vision and ability to execute.
Watson Discovery is IBM’s AI-powered search engine that understands and serves answers from complex business content with context. Watson Discovery delivers answers on-demand and proactively via simple natural language search, leading businesses to insights hard or impossible to derive otherwise.
Watson Discovery stands out from its competitors because of easy-to-use graphical training interfaces that enable non-developers to leverage AI to transfer their knowledge to the system -– making Watson Discovery even smarter when dealing with company or project specific complex business content:
- Smart Document Understanding is Watson Discovery’s capability that enables subject matter experts to teach the system where answers and other relevant information reside inside of content based on the visual layout and formatting of documents.
- Watson Knowledge Studio enables SMEs to teach Watson Discovery the language nuances of specific domains –like product names and other project or company specific lingo.
- Watson Discovery’s relevancy training user interface enable SMEs to teach the system which answers are most important depending on the questions being asked.
With out-of-the-box integration between Watson Assistant and Watson Discovery, answers derived by Watson Discovery can be surfaced through conversational interfaces in any application, device, or channel. This extends the power of Watson Assistant to answer less frequent and/or outlier questions and can enable a faster initial time-to-production since answers from existing business documents surfaced by Watson Discovery do not require dialog creation or intent training.
Enterprise search means higher business value from your data
Developing products and services is something every company strives to do well, but a byproduct of doing business in the information-age is the massive amount of data created every day in the process. Every customer contact, every phone call, chat and email holds information that might be useful for your company. Hidden away in your data are solutions on how to best streamline processes, how to create a more productive workflow for your employees, and how to best serve your end user, but without the right tools and techniques, those insights are in danger of being locked away forever.
As individuals, when we’re looking for solutions, we turn to the internet where a simple search can uncover worlds of insight. Providing information to your employees in a just as thorough and efficient way is important to success, however, searching for business insights in data is a lot like looking for a needle in a haystack. A haystack that’s growing exponentially larger each day, making it impossible for any human to find what they need, and there’s so much data that it’s becoming increasingly difficult for data processing systems to handle. Discovery’s award-winning AI search insight engine is AI doing what AI does best, making predictions, automating time-consuming manual processes and optimizing the volumes of data a company has on hand.
As that data continues to expand, many businesses need a solution that can help both employees and customers find the correct information, make decisions, and complete tasks faster. With Watson Discovery, your business is able to enhance human intelligence using AI technologies like natural language understanding (NLU), machine learning (ML), and deep learning (DL) to sort through ubiquitous data and find specific information. Discovery also learns through relevancy training — both supervised and unsupervised — so it learns through interactions and through manual training by a subject matter expert, making Discovery customizable to provide greater salience within content.
Watson Discovery enables an enterprise to apply AI’s ability to pinpoint relevant data, allowing existing information to be remixed or synthesized, then delivered proactively when the AI thinks an employee will need the info, or in response to a manual search by an employee, offering deep knowledge on demand.
Boost employee engagement with natural language AI search
The success of IBM’s AI strategy is best demonstrated by their client success stories. Across a variety of industries clients have seen positive results while leveraging Watson Discovery; Australian energy company, Woodside, has experienced “75% decrease in time employees spend searching for expert knowledge.” Similarly, Gordon Flesch has experienced significant benefits from their implementation of Watson Discovery, they saw “some user satisfaction levels go from around 0 percent to almost 100 percent.”
Three things to be prepare for when thinking about adopting an AI solution:
- AI is not a magic wand; it takes time and dedication to tailor your AI solution so that it can address your unique use case
- AI thrives on data, build a dedicated team to teach the solution what it needs to know, implement it properly, and deploy where it’s most useful
- In order to get the most out of Watson AI, you’ll need to subscribe to IBM Cloud Pak for Data, IBMs true plug-and-play data and AI platform which allows you to:
- Have one integrated console to collect, organize and analyze your data
- Virtualize your data regardless of where it lives
- Build once and run anywhere across dynamically changing environment
Watson Discovery provides award-winning AI search and natural language processing
IBM Watson Discovery was also named a leader in AI Search by Forrester Research earlier this year and was recently awarded as “Best Innovation in NLU” by AIconics, for its second year in a row.
Gartner, Magic Quadrant for Insight Engines, 17 September 2019, Stephen Emmott, Saniye Alaybeyi, Anthony Mullen 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, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.