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Solving the search problem with finely grained information sans the cruff

The Real Time Matrix's Jon Sofield and I spoke with Dennis Howlett about how precision persistent search can be used in the enterprise to filter signal from noise. Apparently we struck a chord based on his post on his blog AccMan: Solving the broken search problem.

I pulled this over from his blog AccMan

“How often have you searched on a term. only to find that 50-50% of what Google serves up is totally irrelevant? I reckon about 10% of my site traffic turns up by accident, largely because of a Google search…

I spoke with Scott Niesen, director of marketing at Attensa and Jon Sofield of Real Time Matrix the other evening to figure out what this means and how it works. Real Time Matrix, which, according to its blog is tapping into more than a million items per day, delivers only the news you want. This, from RTM???s site:

Conceptually, it???s pretty simple: take millions of live content feeds and correlate millions of preferences for content against them in real time. When an ???item??? matches within an acceptable coefficient, deliver it to any Internet-connected device.

In practice it isn???t though RTM has solved the riddle. Attensa turns this fine grained information into an enterprise RSS feed allowing the user to effectively mash up the most appropriate information required for the task in hand from any source.”

In our conversation Dennis reeled of vertical after vertical where real time information is business critical. His list includes: brokerage house trading floors, pharmaceuticals, telcos, utilities and any business that want meaningful competitive and market intelligence. These businesses would all benefit from precisely honed searches that deliver “fine grained information” while eliminating irrelevant “cruff” ( in Dennis' parlance.)

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