‘Cognitive Search’ May Be the Sector to Watch
In our data-driven world, the ability of large businesses to locate pertinent facts quickly and automatically from their growing stores of information can deliver a competitive edge.
On an individual level, we have all grappled with the frustrating experience of trying to enter just the right keyword or combination of letters and numbers to get to the exact bit of data we need. But as data multiplies continuously in libraries and archives, a new sort of search with the ability to cut through the chaff is coming into its own. It’s called “cognitive search.”
As the term suggests, the “thinking” is deeper than that in a traditional keyword search. It’s leveraged by artificial intelligence and machine learning and gathers insights from signals and behavioral data. The insights can come from activities such as employee visits to web pages, their interactions with each other via chat media or the documents they produce and store.
Vast amounts of wasted data
Research from Forrester suggests that vast amounts of corporate data are going to waste. Between 60% and 73% of the information held by a corporation goes unused or unanalyzed. And a little more than half of all IT workers — 54% — are interrupted from their daily routines several times each month to search for information, adding to company inefficiencies, the research concludes.
“Keyword-based enterprise search engines of the past are obsolete,” Forrester says. “The new generation of enterprise search solutions employ AI technologies such as natural language processing and machine learning to ingest, understand, organize and query digital content from multiple data sources.”
With a separate report from Markets and Markets predicting that the global cognitive services market will expand to some $15 billion by 2023 from $2.5 billion last year, it’s little surprise that the large tech companies are getting into the market.
Amazon’s Kendra
In December, Amazon Web Services, the sector’s leader, unveiled the Kendra service to take on similar search products from Microsoft and Google. Amazon said its intuitive searches use natural language queries leveraged by machine learning algorithms to comb automatically through an organization’s data sources to get results with a high degree of accuracy.
With Kendra, the company says, you can provide pinpoint search accuracy from content within manuals, research reports, customer service guides and others. All you need to do is plug and play with no need for machine-learning expertise.
For now, Kendra is only available in northern Virginia, near Washington D.C., Oregon, Amazon’s headquarters, and in Ireland, its European base. When the service is fully operational in the future, it will come with connectors to products including Box, Dropbox, Salesforce and Microsoft’s OneDrive.
Microsoft’s Project Cortex
At about the same time, Microsoft unveiled its Project Cortex for trials. It’s something of an evolution from Microsoft Search tools used with its Bing search engine to generate silo-type searches in Outlook email or Word documents.
Instead, Cortex, which Microsoft publicizes as the fourth pillar of its Microsoft Office software package, uses machine learning to generate content based on documents and social network conversations.
Cortex uses artificial intelligence to scan content across teams and systems, recognizing content types, extracting information, and automatically organizing content, Microsoft says. Cortex then creates what it calls “a knowledge network” based on relationships among topics, content and people.
The cognitive search segment is already healthy, with Google having launched a “Cloud Search” product in 2018. Others in the sector include IBM, Hewlett Packard Enterprise and several start-ups, Attivio, Coveo, Lucidworks and Squirro.
But, as data generation continues to grow, systems that can mine all this data for corporations are poised to grow along with it. It’s definitely a market to watch.
