Inform Technologies, Inc.
HQ: New York NY, USA
Products (Primary): Inform
Contact: Josh Kirschner
Vendor Category: NLP
Installed base: --
It’s safe to say that Inform has built a successful business by using NLP technology to process its customer’s Web sites and then enrich these pages by linking to relevant content published elsewhere on the Web. One look at Inform’s customer list, which includes names like Ziff Davis, The Economist, Wired, and many more serves as solid evidence that the company has a winning product. Each of these customers has decided that it’s in their best interest to seek out relevant external content and then publish it to supplement the original article on the page.
Increasingly, publishers seem motivated to engage in this practice in the belief that it reinforces their authoritative standing in the eyes of their audience. As would be expected, customers can control what external content is deemed suitable for publication on their site by creating white lists and black lists, as well as whether or not to keep visitors within the publisher’s “family” of media properties.
In practice, using Inform’s solution is easy enough – Inform hosts the back end where the processing is performed, and when a publisher creates an article its submitted through Inform’s API. The article is processed, the (desired) relevant content is identified and linked, and the results are returned to the customer for final publication. Aside from expanding the content presented to visitors, these results also play an important role in Search Engine Optimization (SEO), with customers reporting page views increasing by 10% to 20% and in some cases as high as 25%.
In the course of its existence, Inform created a well developed, professionally maintained taxonomy. This complements the work of the company’s library scientists, linguists, and ontologists and has had the effect of positioning the company well to pursue specific vertical markets such as health. As a result, Inform is prepared to move into select industries and may well do so from a position of strength, unburdened by the need to play “catch up”.
A very interesting (and fully operational) example of just how far Inform’s solution can be extended is found at NewsDaily.com. Reportedly, this site is operated by a single individual who uses a Reuters feed subscription to form the content kernel for processing by Inform. Clicking through the top-level Reuters content leads to pages the clearly include related articles from a wide range of publishers. Readership or audience numbers weren’t supplied, but the low fixed costs of this business suggest that modest advertising success could yield solid revenues for a one man operation.
Six/Twelve Month Plans:
Aside from its potential entry into specific verticals, Inform is considering opportunities in advertising. While it’s easy to imagine the extraction of primary concepts from an article and then associating relevant advertisements, the actual implementation has challenges which Inform has yet to fully define. Aside from these two possibilities, Inform is deep into execution mode and at this point, a primary goal for the company is to continue building on its track record of success.
Inform has a roster of believers who have contracted for their services. In many ways, the business case is fairly easy to express – in a traditional publishing environment there might be a number of editors who spend part of their time tagging stories for a variety of reasons. Time spent tagging means time taken away from other, higher value activities. Inform’s solution reduces this burden on content editors which translates into time savings, cost savings, and higher productivity (arguably, these are all ways to describe the same business result). These savings, combined with an improved audience experience, create a compelling argument for publishers to take a close look at this technology and how it fits with their overall goals.