Inform provides media websites with a technology solution that automatically searches, organizes and links content to provide the site with depth with the aim to win and retain more readers. The easy-to-implement technology automatically creates links to relevant information on the site, in archives and anywhere on the web, to create a more detailed reading
SM: Let’s discuss your financial history, in the final segment of the conversation. Who financed the company at the very beginning? I assume it was some of Neal’s Capital IQ proceeds that went into Inform. JS: It was friends and family, yes. SM: Did you raise Venture money? How much? From whom?
SM: What is the business model of your company? JS: As I showed you, Sramana, we have 2 different business models, one a fee-for-service model that has a consistent, recurring revenue stream, and a revenue-share, ad-based model, which is more consistent with the lighter implementation of our products that I demoed for you. SM: What
SM: What is your personal background? JS: I have an undergraduate degree in computer science with a specialization in artificial intelligence and natural language processing. I also have a graduate degree in business (an MBA). Both degrees are from Columbia University. Prior to joining Inform, I was the CEO and President of C.E. Unterberg, Towbin,
SM: What is your target customer? (Please provide a good segmentation perspective) JS: Our target clients include publishers and information providers who seek to maximize the value of their content. Many of these publishers support a network of properties, and employ Inform’s technology to offer more value to their users across sites. We also operate
It turns out that both Jim Satloff and I happen to be Artificial Intelligence aficionados. What you read here is a discussion on Inform’s Natural Language Processing (NLP) based technology that attempts to create an interesting value proposition for publishers on the web. AI has been a notoriously difficult technology genre with big promises and