Jul

nmodes Technology - Overview

                                                       

nmodes ability to accurately deliver relevant messages and conversations to businesses is based on its ability to understand these messages and conversations. Once a system understands a sentence or text, it can easily perform a necessary action, i.e. bring a sentence about buying a car to the car dealership, or a complaint about purchased furniture to the customer service department of the furniture company.

Understanding sentences is called semantics. nmodes has developed a strong semantic technology that stand out in a number of ways.

Here is how nmodes technology is different:

1. Low computational power. We don’t use methods and algorithms deployed by almost everyone else in this space. The algorithms we are using allow us to achieve high level of accuracy while significantly reducing the computational power. Most accurate semantic systems, e.g. Google’s, or IBM’s, rely on supercomputers. By comparison our computational requirements are modest to the extreme, yet we successfully compete with these powerhouses in terms accuracy and quality of results.

2. Private data sources. We work extensively with Twitter and other social networks, yet at the same time we process enterprise data.  Working with private data sources means system should know details specific only to this particular data source. For example, when if a system handles web self-service solution for online electronics store it learns the names, prices, and other details of all products available at this store.  

3. User driven solution. Our system learns from user’s input. Which makes it extremely flexible and as granular as needed. It supports both generic topics, for example car purchasing, and conversations concentrating on specific type of car, or a model.

Interested in reading more? Check out our other blogs:

WHY ALL CONVERSATIONAL AI SOLUTIONS ARE CURRENTLY CUSTOM MADE

                                                                                                                                         

All quality conversational AI solutions such as chatbots, voice bots, virtual assistants are customized. The reason is because conversational AI solutions have a component called AI training that has to be individually tailored to the needs of each business. Currently AI industry does not have a suitable solution to automate this component.


There are, of course, easy-to-use, scalable products such as Chatfuel, ManyChat and others, but they do not provide sufficient quality and therefore do not add value to the professional sales or customer service process.


The next generation of conversational AI solutions will be scalable, while capable of delivering the level of quality required by businesses and professional organizations. nmodes is among a limited number of AI companies, with sufficient level of technological knowledge and deep enough understanding of underlying linguistic processes. working on delivering this kind of solution to the market as quickly as possible. In the meantime, customizable AI solutions, with personalized AI training component, is industry's best option.  

 
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MAKING AI MAINSTREAM



We are experiencing a strong demand for conversational AI solutions. It is coming from every corner of the B2C market. It is growing by the day.

Conversational AI is becoming increasingly popular among the consumer facing business community. It is easy to see why - AI offers sales and customer service scalability and therefore is critical for the long-term success of a business.

Conversational AI solutions such as chatbots, voice bots, and virtual assistants provide much needed speed and efficiency, in an age where the rapid advancement of technology makes them virtually the only sustainable customer service solution.

Bu there is a catch - AI is complicated. Mainstream businesses do not have in house AI expertise. And it is not part of their business model to develop such expertise.

Today’s market offer several good conversational AI solutions, such as IBM Watson or Google DialogFlow. However, getting a business value out of them requires the very AI expertise that mainstream companies do not possess.

So what can be done?

Any AI solution should follow these three steps in order for the mainstream business community to fully benefit from it:

  1. Conversational AI should come as a service,
  2. The service should be available in natural language,
  3. The service should be fully personalized.  
 In the next several posts we will explore how the AI industry, including nmodes, is moving towards achieving these goals.
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