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7.9.10 - nTeligence Corporation
has acquired the intellectual property portfolio of Mobile Agent Technologies, including their trade secrets for Common Sense Reasoning and patented approach for the seamless migration of running software programs based upon ever changing environmental conditions. The merged entity will do business as nTeligence Corporation and will be led by an executive team taken from both of the former companies. The core services of the newly merged firm will be the design and development of customized virtual assistants, intelligent advisors, strategy engines that optimize business outcomes, and product recommendation systems.

 
2.6.08 - Common Sense Reasoning. Mobile Agent Technologies has introduced software technology that enables computers to think, called Common Sense Reasoning. The technology simulates human cognitive processes, such as intuition and gut feelings, on a computer. Up until now, human intelligence has been missing from core line of business applications. Read Press Release

7.25.06 - Automatic Thread Migration
The USPTO has formally issued Mobile Agent Technologies a patent for its innovative means to automatically relocate running software programs, from one machine to another on a heterogeneous network, based upon ever changing environmental conditions. This new approach makes process migration invisible to the application developer. Uses for the technology include massively scalable, fault tolerant, high performance distributed computing systems. This includes applications that rely upon complex mathematical algorithms and business rules, which exhibit human like intelligence.

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Machines That Think

The first fifty years of the information age was focused on business systems that were transactional in nature. The next fifty will be about building machines that can think. This includes intelligent advisors, virtual assistants, strategy engines which can optimize business outcomes in real-time, and systems that make product recommendations in order to drive new revenue streams. Each of these types of systems multiply the intellectual capacity of an ever shrinking corporate workforce.

The first foray into the field of "smart software" by organizations took place in the mid 1980's. At that time artificial intelligence garnered a great deal of press, especially expert systems that could diagnose medical conditions, approve credit card purchases, and configure complex computer systems. Although these systems were technically sound and provided economic value, initial successes did not lead to widespread adoption. This was due to system integration issues, the arcane nature of the programming languages that were used, and the basic fear from skilled workers that they might be replaced.

In the nineteen nineties, another approach to building smart systems emerged, that of using mathematical algorithms and data analytics, to help forecast business outcomes. Today these types of applications predict which customers will respond favorably to a given marketing promotion, are most likely to cancel their service, or file a fraudulent claim. Although current analytics applications play a vital and cost effective role in today's enterprise, they are not capable of intelligent thought. They are limited by their inability to reason, logically deduce new facts from existing ones, match patterns found within their environment to past experience, and learn from their mistakes.

There is a significant "functional gap" left open by today's business intelligence (BI) software suites. A recent survey conducted by Information Week magazine found that only nineteen percent of companies using business intelligence software were actually successful in improving their performance. The core subsystems of these product suites provide an overwhelming amount of information to decision makers, either in the form of reports, dashboards, or through drilling down into "cubes of data", without ever explaining what it all means. This information essentially amounts to a "rear-view mirror" look at business activity within an enterprise. Existing performance management suites on the other hand, attempt to identify key organizational metrics which are related to profitability, but also fall short in their ability to know what the future has in store. Just as important though, these applications can not recommend what course of action to follow as business events occur in real-time.

Both business intelligence suites and performance management software lack the innate ability to optimize each individual outcome, as potentially thousands or even millions of transactions occur every minute for a given company. In these tough economic times companies need to be able to look clearly through the front windshield at the road ahead, and be able to take immediate action to seize each and every business opportunity, before one of your competitors does. In the internet age a millisecond is all it takes to convert a prospect into a new client, or perhaps lose a very profitable and valued customer. This is the type of power that Einstein Enterprise willl provide your organization with.

Over the past ten years there has been an overwhelming trend in the software industry towards "professional" open source products, which provide the equivalent features and functionality of oftentimes very expensive commercial offerings. To draw a parallel to the pharmaceutical industry, open source software is like a less expensive generic drug that has now become available because a patent has expired. Why pay two million dollars for software licenses from five separate commercial vendors, when you can effectively have a fully supported "generic equivalent" from a single vendor, for a mere fraction of the cost?

nTeligence Corporation has incorporated this basic fact into our business model. Our strategy combines our own proprietary software technologies with a number of open source initiatives. This compelling business model allows us to deliver a cohesive platform for building intelligent systems for about one tenth the cost of similar commercial products. As the average personal computer is used less than ten percent of the time, we can also "re-purpose" unused CPU cycles and memory on dozens, or even hundreds, of existing desktop PC's throughout your organization. Creating a "virtual supercomputer" using unused CPU cycles on computer hardware that your firm already owns is a very smart business decision.

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