Integrated intelligence
for every moment

Four Unique Assistants

Forget about bots or fancy forms, let me tell you how this works. First we build a database of information about you or your products and services. This can be real-time data, customer information or operational systems. Then we model solutions from human interactions to create the finest user experiences and actionable content - real AI. Sometimes these experiences are verbal interactions, sometimes they have an immersive user interface, and we are pioneering methods where we can build all these into one seamless lifestyle. We can even have your systems learn and evolve.

Where it get interesting, is when the assistants assist each other and you integrate live, work, play and operate into one seamless experience. Each assistant has a different function and data access that must be protected, so privacy comes first. Our approach shares information only by necessity and only for the moment to allow a brand or business or be able to personalize and respond in real-time to discovery, location, safety, security or automation requests. All of this is possible with the latest serving of technology from where Big Data, AI, and IoT comes together with deep learning and modern mobile and web designs.



Brand and Store Bot

PAL @ Work

YVE — “yeve” Your Virtual Enterprise

An AI-powered virtual assistant to manage and improve business operations. YVE lowers operating costs and improves efficiency by using AI-powered information architecture and statistical models to provide business insights and recommendations, while automating workflow and increasing supply chain efficiency. YVE effectively eliminates intermediaries allowing your business to operate at its highest potential.

More Info →
New urgent maintenance activity created 12:34PM [UMA:4530]
The water tower pump [ID:456710] located at [Neon Lofts Rooftop] is failing. I have contacted the distributor for parts status.
Update 13:41 PM - Yve
[Pump Motor] available and [John Smith] is closest technician to location, shall I dispatch for parts pickup?
Update 13:41 PM - Yve
Assign [Bill Evans] to meet [John Smith] at rooftop at 3 PM.
14:45 PM - Chief
14:46 PM - Yve
Can I trash the old motor it is burned up bad, won’t get any core deposit back?
15:30 PM - Bill Evans
No problem
14:46 PM - Yve
Update - Status change to closed.
16:40 PM - Yve Pump Motor replaced.
15:32 PM - Chief

PAL — Personal Assistant Liaison

We are developing a self-learning assistant for every citizen on the planet. This assistant will evolve over the next several years to become self-learning and react to situations in near real time. It will seamlessly integrate with your brand, work and location assistants.

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Where can I find a quick and healthy lunch nearby?
There are 10 great spots that also have gluten free options. Here are 3:

PAL @ Work

For coworking and as part of the Concept Foundry platform, PAL@Work provides all the features to help operate a business including an AI assistant to guide your members, create community and provide a great environment for your members to grow a company. One platform to deliver public, member, admin web and mobile experiences fully integrated with the community through our smart district overlay.

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Book a conference room
At what time and for how many people?
Noon today and for 10 people
Here are a few options based on your preferences.

Brand & Store BOTS

You can add the PAL experience to your store or brand. We want to restore the benefits of knowing your customer through conversation. We provide tools to create tailored interactions that lead to great experiences. Every business, large or small, can have their own affordable AI assistant that builds loyalty and learns and adapts to your customers.

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Introducing the next iteration of speaking to brands.
Content, information, and ideas tailored to you with a simple conversation.

How does it work?

There are two engines that operate and work together to integrate live work play and manage into one cohesive system. The Moment Manager looks after citizens and people where it can provide information or advice to create a better experience and the Insight Manager looks after physical locations, assets, operations and data that can be used to improve efficiency and business outcomes.

Insight Manager

The Insight Manager utilizes deep learning models and predictive analytics to provide insights with situational awareness. It can be used within dashboards by analyzing KPIs in a way to look for indicators that may provide predictors for future performance. Depending on the skill, information is gathered and run against industry norms so that a score can be generated. These norms may be parametric boundaries or trends or complex models. They are run based on either scheduled timing or a specific event.

Moment Manager

We take little pieces of information and develop a picture of you as a person using a learning algorithm. This is possible by mapping nonspecific information in a way that gives us insights to the person’s activities and experiences. We build a moment where the moment manager can evaluate the intents and decide when and how to create a better experiences and learn from ones that don’t work out. As PAL learns it will use information gathered from similar people to understand cultural nuances and not make foolish mistakes. This correlation period will take some time and our goal is to have 100,000 people in training within the next 18 months.
How to build an Insight
Insights are critical to the success and optimization of any system or organization and can be found in strange places. Here are a few examples to illustrate creating a condition:action scenario:


a motor that has no digital interface but the current draw can be measured through IoT and a variation has gone up or down by more than 3% over a period of at least X days and that signals an impending failure.


a QA insight that could be looking for outliers by combining information not normally joined together. For example by reviewing and correlating reviews from multiple sites you might find scattered data about food complaints that happen at various times, but are more frequent at one location and merging that data against work records yields the outlier and the same line cook and the problem becomes obvious.


perhaps in store conversions are something that needs your attention and this can be accomplished human less where a camera could be setup outside and inside your store to establish gender / age conversion bias from walking into the store, basically whom is attracted to your windows or adverts and whom is walking by without invading privacy.