The biggest text analytics company you probably never heard of
I caught up with Expert System S.p.A. last week. They turn out to be doing $10 million in text technology annual revenue. That alone is surprising (sadly), but what’s really remarkable is that they did it almost entirely in the Italian market. As you might guess, that figure includes a little bit of everything, from search engines to Italian language filters for Microsoft Office to text mining. But only $3 ½ million of Expert System’s revenue is from the government (and I think that includes civilian agencies), and under 30% is professional services, so on the whole it seems like a pretty real accomplishment. Oh yes – Expert Systems says it’s entirely self-funded.
As of last year, Expert System also has English-language products, and a couple of minor OEM sales in the US (for mobile search and semantic web applications). German- and Arabic-language products are in beta test. The company says that its market focus going forward is national security – surely the reason for the Arabic – and competitive intelligence. It envisions selling through partners such as system integrators, although I think that makes more sense for the government market than it does vis-a-vis civilian companies. In February the company is introducing a market intelligence product focused on sentiment analysis.
Expert System is a bit of a throwback, in that it talks lovingly of the semantic network that informs its products. This semantic net was assembled in the usual way – start with WordNet, add a huge number of proper nouns, license a bunch of domain-specific dictionaries, and handcraft further as individual customers require it. In English the whole thing has 300,000 nodes and 1.2 million relationships.
Expert System insists that there’s a secret sauce in how the semantic net is organized, to optimize performance. But I haven’t gotten the slightest hint of what that magic data structure is — despite having asked more than once – and so have to reserve judgment on that part.
On the search side, Expert System sounds fairly rich in terms of deciding relevancy, going beyond Term Frequency/Inverse Document Frequency + synonyms. Terms are also assigned importance by their grammatical roles, such as whether they’re sentence subjects, sentence objects, in paragraph topic sentences, and so on. Of course, the whole concept of exploiting grammatical structure is a bit old-school. Specifically, it presupposes you’re looking at decently grammatical documents in the first place, which can be a dubious assumption in the era of “im in ur cuzztom3r bazz eatin ur r3venue$z.”
The most interesting application Expert System told me about was one for Pirelli Tire, scanning the web for prices Pirelli products were sold at, to detect gray market activity. Web-crawling for text analytics and price detection are both major activities – e.g., QL2 is active in both – but this is the first I’ve heard of the areas being so tightly integrated.
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