Insights into Inbenta – Providing Artificial Intelligence for the Enterprise

I recently had the opportunity to learn more about Inbenta, a provider of Natural Language Search technology for intelligent assistant and web self-service technologies. I spoke with global marketing director Julie Casson and Kelly Foster, linguist, to gain insight into a company I didn’t know much about. Inbenta originated in Barcelona, and now has offices in the United States, France, Singapore, Brazil and the Netherlands. Casson and Foster are located at the office in Sunnyvale, California.

Inbenta VictoriaPrior to our conversation, I knew that Inbenta offers intelligent assistant technology and an extremely innovative 3D avatar, called Victoria. I’ll talk more about Victoria in a moment. But first, I’ll summarize what I learned about Inbenta’s underlying technology.

I asked Foster what drives the Inbenta intelligent assistant natural language processing engine. It turns out that Inbenta has its own powerful semantic technology that the company has developed and cultivated over many years. The semantic engine runs atop a proprietary lexicon that enables Inbenta’s search and virtual assistant technologies to perform complex natural language processing operations.

As a linguist, Foster knows a lot about how languages work. She explained to me that the Inbenta semantic search engine is based on something called the “Meaning-Text Theory,” which was developed by Igor Melchuk and Aleksandr Zolkovskij. There’s a whole page on the Inbenta website that describes the basics of Meaning-Text Theory. There’s also a description on Wikipedia, which I suppose means it must be real! My wildly oversimplified explanation of the theory (and please don’t quote me on this, in case I’ve got it all wrong) is that all languages are comprised of lexical units, and that these lexical units can generally be categorized into a finite number of lexical functions. Lexical functions are the basic building blocks of language that define semantic relationships between concepts, and that ultimately allow us to use language to create meaning. You can find examples of lexical functions here.

Inbenta has created its comprehensive semantic search engine using the Meaning-Text Theory approach and the lexicon is available in many different languages. The fact that Inbenta doesn’t have to rely on a third party for its natural language processing technology means that it can offer customers a rich feature set, while maintaining its independence and continuing to enhance its product at its own pace.

So how does Inbenta position itself in the web self-service/intelligent assistant market space? Casson says the company is focused on providing businesses with tools to improve customer support. They offer everything from a strong search engine that users can access to find answers to tough questions, to full-blown intelligent assistants. Using these technologies, customers can find answers themselves, freeing up human call center agents to focus on more complex and important customer inquires.

Which brings us back to Victoria. When you visit Inbenta’s website, you’ll see a large white question mark surrounded by a circle. Click on the question mark and Victoria, a remarkably lifelike human avatar, appears. It turns out that Victoria was created in response to a request from Telefonica, a large Spanish broadband and telecommunications provider and major customer of Inbenta. Victoria responds to text input and she can deliver her responses in written or spoken form. Once she is connected to a knowledge base, she can search through information to find responses to customer inquiries. The version of Victoria that’s on Inbenta’s website isn’t plugged into a large knowledge base, so conversations with her are pretty limited. But you can get a general idea of how the technology works. While Victoria’s gestures and motions can be a little distracting at times, the avatar clearly represents an innovative technology with lots of possibilities. It’ll be interesting to see how Inbenta’s 3D avatar evolves and how companies leverage the technology to more effectively engage customers.

As I learned from my discussion with Casson and Foster, Inbenta has a lot of things going for it. Its proprietary semantic engine can drive powerful language processing. Its unique 3D avatar has many possibilities to enhance customer support. Its broad existing customer base, which includes companies such as Schlage, Groupon, and Ticketmaster, give it the experience to implement effective web self-service solutions. Inbenta is certainly a company to consider if you’re in the market for customer-facing intelligent assistant technology.

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