Enkia: Early Player in Smart Search
May 26, 2009
Last week, I received a call from a defrocked MBA looking for work. (No surprise that!) The young wizard wanted to know about Enkia, a spin out of Georgia Tech’s incubator program in the late 1990s. If you poke around Web traffic reports, you see a surge for Enkia in year 2000 and then a flat line. In November 2008, a person sent this Twitter message that plopped into my tracking system: “Enkia is alive.” I told the job hunter that I would poke through my search archives to see what information I had. I will be in Atlanta in June, and I will try to swing by the company’s office at 85 Fifth Street in Atlanta to see what’s shakin’. (The last time I tried this approach the TeezIR folks kept the door locked. Big addled geese are often not welcome. Gee, maybe it’s because the addled geese don’t believe the chunks of marketing food tossed at them by vendors.)
According to an August 2000 article here, the company was
building the foundation of the Intelligent Internet(TM) based on the latest discoveries in cognitive science and artificial intelligence. Enkia’s middleware products overcome the limitations of current Internet search technology by sensing what a browser or shopper wants and recommending information quickly and automatically. This software enables portal providers to create personalized experiences that encourage return site visits and increased sales. Founded in 1998, Enkia is a member of the Advanced Technology Development Center (ATDC), the Georgia Institute of Technology’s high-tech business incubator.
What It Does
Enkia, the name of a Sumerian god with special brain power, was an early entrant in the “artificial intelligence for the Web movement”. If you have been following the exploits of Google, Microsoft, and Yahoo, the notion of smart software is with us today. The marketing verbiage is different, but the notion is the same as it was for Enkia.
Here’s a description from a year 2000 business journal story:
The software [Dr. Ashwin Ram and his students developed, called Enkion, has a type of ESP, if you will, sensing browsers’ needs by what they click. Enkion builds on techniques of artificial intelligence to model the human mind. The technology automatically recommends relevant information so that users don’t have to wade through hundreds of search results.
The company put a demo online, and I had a screen shot of the service. I thought I had results screen shots, but my memory deteriorates more quickly than the value of a US government Treasury note.
Screen shot of the Enkia Search Orbit interface, no longer available.
When the service rolled out, Dr. Ram said here:
“EnkiaGuide helps anyone find their ‘needles’ in haystacks of data on and off the Internet,” Dr. Ram adds. “It can help users find their way through technical support libraries or large e-commerce sites, and allow corporations to organize pathways through their large proprietary databases. The EnkiaGuide can make sense out of information chaos.”
In my archive, I had a copy of an older white paper which is still available online as of May 25, 2009, here:
The IRIA architecture builds upon and extends the experience-based agent approach by embedding it in a knowledge discovery and presentation engine using techniques from artificial intelligence and machine learning. Crushing demands on resources limit the amount of “smarts” typical web search engines can apply to any particular information resource requests. IRIA’s design overcomes this problem by leveraging existing search engines for the brute force work of indexing and searching the web and by focusing its “smarts” on modeling and understanding the efforts of an individual or workgroup. The core of IRIA that makes this understanding possible is its reminding engine. The reminding engine directly applies the experience-based agent approach to the problem of information search, consisting of a context-sensitive search mediator which uses a unified semantic knowledge base called a knowledge map to represent indexed pages, queries, and even browsing sessions in a single format. This uniform representation enables the development of an experience-based map of available information resources, along with judgments about their relevance, allowing precise searches based on the history of research for an individual, group or online community. The knowledge map is furthermore a browsable information resource in its own right, accessible by standard internetworking protocols; with appropriate security precautions, this enables workgroups at remote sites to view and exploit information collected by another workgroup.
You can locate the Enkia Web site at www.enkia.com. There are contact details, the names of some of the employees, and basic information about the companies products. The company offers a simplified diagram of the system architecture. It provides little information, but I will include it for your reference:
Source: Enkia Corporation.
I also had a more detailed explanation of the plumbing for the system. You can find the description or IRIA or Information Research Intelligent Assistant here:
Enkia Corporation’s IRIA (Information Research Intelligent Assistant) technology is a revolutionary new approach to intelligent information management. IRIA is a proprietary artificial intelligence (AI) toolkit that provides intelligent information management (IIM) capabilities for interactive knowledge-intensive applications, enabling developers to use recent techniques from artificial intelligence and cognitive science to provide advanced information capabilities to users in a natural, user-friendly manner. An IRIA-based web research assistant can unobtrusively monitor a user’s browsing activity and suggest “hot” items, enabling users to quickly drill through hundreds of results to find the ones relevant to their interests. IRIA is based on a novel information retrieval architecture that uses memory models from cognitive science for search and mapping, embedded in a knowledge discovery and presentation engine using techniques from artificial intelligence and machine learning.
I don’t have too much information about the company’s finances or its customers. I learned from my notes that the firm obtained money from various Federal government agencies, including the US Air Force. Cox Interactive Media invested a couple of million dollars in the firm. I also found a note that Enkia wanted another $8 million along with a memo I sent to one of the banks paying me for analyses in the 2000-2001 period. GE also signed on with Enkia. I located this description of that deal in my files:
General Electric used case-based reasoning for gas turbine diagnostics at their monitoring and diagnostics center in Atlanta, GA. This application had requirements that included accuracy, maintainability, modularity, parameterization, robustness, and integration of the system into an existing infrastructure. The CBR system has a modular plug-and-play architecture to facilitate experimentation and optimization. It was integrated into the production environment in 2004. The CBR system is currently in a trial deployment where diagnoses made by the system are created along with the previous process of using human-generated diagnosis.
Enkia’s founded said to Red Herring here:
“When a turbine dies we tell (GE) what’s wrong with it,” Dr. Ram said. “The [computer] isn’t preprogrammed with past failures—it learns as it goes.”
As I reviewed my notes from eight years ago, I was interested to see the similarities in some of the descriptions of features. These echoed what I recalled hearing about Fast Search & Transfer and Bing Kumo. Maybe it is prime time for Enkia-style artificial intelligence.
Stephen Arnold, May 26, 2009