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QuickAI, a Practical Solution for AI at the Edge

In our November quarterly conference call we forecasted that we would report our first material revenue for QuickAI in Q4 2018; several quarters ahead of the outlook we provided in May. This led to numerous questions from QuickLogic investors that we could not answer at the time due to the NDA with our customer. We answered some of these questions with a press release last week. If you’ve not seen that press release, you can read it by clicking here.

This was actually the result of years of work done by our first QuickAI customer, mtes Neural Networks (mtesNN). Founded over three and a half years ago, mtesNN has focused on what it terms as the “practical application of IoT” that leverages the power of artificial intelligence (AI) at the edge. After evaluating numerous potential AI solutions, mtesNN chose QuickAI.

AI and IoT are terms often used to paint pictures of vast new market opportunities. While the market opportunities are obviously vast, the OEMs that want to develop products to pursue the markets face many challenges when it comes to delivering a practical solution – a solution that provides value to the customers that will buy AI enabled edge devices and on to the end users.

The design wins we announced with mtesNN are our first examples of how QuickAI enables OEMs to deliver the Holy Grail of a “practical” solution for local AI in endpoint applications. We are very excited about the potential of our relationship with mtesNN, and with the 2020 Olympics rapidly approaching, its aggressive schedule to deploy AI in a variety of edge devices.

In conjunction with a press conference mtesNN held in Japan on November 21st, mtesNN issued a press release announcing the conference, the introduction of mtesNN’s new AI Makibishi cognitive camera & Alcus Crime Prevention Street Light and the broad working relationship mtesNN has established with QuickLogic.

As you can see from browsing the mtesNN website, mtesNN is a highly innovative company that has a number of edge / IoT initiatives that can be enabled by QuickAI. These include cognitive cameras, structural health monitoring, energy health monitoring, human health monitoring and what mtes calls, “IoT Platform Apricot.” You can learn more about these initiatives by clicking on the “floating balloons” you will see on the home page of the mtesNN website. Please use the translation feature of your web browser to view this and other web links above in English.

If you attend CES this January in Las Vegas, you’ll be able to see the mtesNN AI Makibishi cognitive camera & Alcus street light that will be displayed in the QuickLogic suite. Executives from mtesNN will also attend CES to meet with their ecosystem partners and spend some time in our suite. For an appointment at our suite, please email

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