AI 2.0

Eventually the initial phase of your organization's road to adopting AI technology will come to an end. At that point you will need to cross the proverbial chasm and begin to build smarter, faster, more reliable, and safer AI applications, at a lower cost, and which will provide a higher rate of return on investment (ROI). To attain this goal you will need to use the right hardware, software infrastructure, and devleopment tools. As well as a trusted partner to guide you through the next phase of your AI journey. At nTeligence we are pioneering this next generation of core capabilities. We are already building our own dedicated AI hardware, called the Model T, which is based upon powerful, state of the art 64 core CPU's and 10,496 CUDA core GPU's, which are liquid cooled. We are actively working on ways to to seamlessly combine the benefits of mathematically driven decision making, along with the simulation of human like reasoning and thought processes. We call this new and improved form of "thinking" Hybrid Intelligence(tm). In the field of conversational AI, we are working on True Meaning(tm), the means by which a computer can comprehend and fully understand both written and spoken words. We are also developing ways to imbue intelligent virtual assistants (IVA) with Common Sense(tm), something you and I just take for granted. In addition we are leveraging academic research to give machines the ability to learn from their own experiences, as well as by talking to others (humans as well as IVA's). For additional information, or to learn more about how nTeligence can enable you to leapfrog your competitors, please email or simply call 609-651-0070


AIOS is an artificial intelligence operating system. It seamlessly combines intelligent process automation, machine learning, natural language processing, and operational decision management. It was designed to be a fully integrated platform upon which to build the next generation of AI 2.0 applications. Programs developed using AIOS can function as recommendation engines ....                   ,

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eWorkers (electronic workers) are the next logical step after Robotic Process Automation (RPA), which is focused on performing rote manual tasks, such as replicating keystrokes. In human evolution, Homo Sapiens replaced Neanderthals. In a similar manner, eWorkers will supercede RPA in the digital world, and begin to automate tasks that require thinking...

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The Model T is the world’s most powerful, advanced, fully hardened computing appliance. It is dedicated solely to building and running AI applications, and is designed to be deployed at the very edge of the computing network. The Model T incorproates both a state of the art 64 core CPU, as well as a corresponding 10,496 CUDA core GPU...

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nTeligence provides a complete set of advisory services related to the strategic adoption and use of artificial intelligence within corporate, medical, governement and military organizations. This includes a future state software archiecture, a roadmap to adoption, building working pilot applications, and performing core outsourced AI R & D activities on our customers behalf...      

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  • NLU-1 Appliance nTeligence has just released the NLU-1, a computing appliance dedicated to natural language processing and understanding. It can be used as a complete turnkey platform on which to build and deploy robust, state of the art, conversational AI applications, Or as an alternative, it can be used to fill capability "gaps" within your existing chatbot or intelligent virtual assistant environment. One use case would be to build and deploy more accurate, industry specific, intent recognition models. For one client, the custom deep learning model we developed reduced their error rate for mis-classifying utterances into intents by a full fifty percent (50%). When compared to the default model being used in production, which was built by their IBM Watson Assistant toolset. Click the link above to view our "video brochure".
  • Recent Blog PostsIn alignment with our goal of maintaining thought leadership in the field of cognitive computing we have begun to write technical blog posts, but in easy to understand layman's terms. The first is entitled "Protecting your Mission Critical AI Applications Against the Coming Russian Cyberattack".
  • eWorker NewsnTeligence Corporation recently unveiled the EWP-1, a self contained platform on which to build and deploy eWorkers (electronic workers). They are the next logical step in the evolution of Robotic Process Automation (RPA). eWorkers have the ability to perform higher level cognitive tasks than their predecessors, and they can learn and grow smarter from historical data, their own experience, and through conversation. If you would like to view a simplified version of an architectural diagram for our eWorker platform, just click on the "eWorker News" link above.

Smarter, Faster, Lower Cost AI

If you are currently deploying, or building, applications that depend upon cloud based AI service offerings, or virtual machines, from IBM, Microsoft, Amazon, or Google, nTeligence can signicantly reduce your costs. This is because our underlying business model is completely different than these cloud based service providers. Along with every pre-paid yearly subscription for AIOS, our Artificial Intelligence Operating System, we will provide you with a Model T computing appliance at no additional charge. Cloud vendors on the other hand typically bill you thousands of dollars per month for each virtual machine that you use, as well as for addtional platform level services, such as a Kubernetes cluster, or their own proprietary web based AI services that your applications consume.

The number one problem for organizations building and deploying AI applications in the cloud is vendor lockin. If the industry shifts to a better, faster, cheaper, more reliable, or smarter artificial intelligence technology (either hardware or software based), and your cloud vendor does not choose to support it, then your organization will find itself at a significant competitive disadvantage. Just one example of this scenario is Amazon AWS' decision not to support the NVIDEA A100/GA102 series of GPUs. Which are now the defacto industry standard for deep and reinforcement learning. In this particular case AWS chose to push their own propreitary GPU design instead, which out of the box will not run custom built Tensorflow and PyTorch models.

To schedule an initial 30 minute conversation, to see how nTeligence can reduce your monthly cloud based AI expenditures, as well as help you to avoid vendor lockin through the use of Open Source Software (OSS) and Common Off The Shelf (COTS) hardware, just write to or call (609) 651-0070

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