INESS creates behavioral maps and produces simulations for improved operational, space, and investment efficiency. The data created from the building is collecting and delivering continuous information about the people inside, how they move, their behavior patterns, and other conditions inside the building.
The mission of INESS360 is to be the world’s leading integrator of behavioral data analytics to predict occupants’ behavior patterns and operational needs in order to deliver a more comfortable work environment, greater profitability, and optimized building operations.
Tell us about yourself?
I started my professional carrier as a Project Manager at Siemens Technologies. After working 5 years in Building Technologies I was appointed as the MENA Region Business Development manager at E-on Ista Holding. During the time I served as Business development manager, I was responsible for the operations in 5 different countries on 3 continents. I set up operation from 0 to 50m Euro revenue in 5 years.
At the time I was working in large corporates in smart building technologies, I experienced that all those expensive systems were not really connected with the real usage trends of the buildings. The technology was as smart as the people that are using and programing it., The effects of human behavior were neglected nearly all of the time.
I decided to move on my own and create a technology that was not focused on opening or closing devices remotely but more on humans and creating an adaptive intelligent system for commercial buildings of any size and any industry.
If you could go back in time a year or two, what piece of advice would you give yourself?
Of course, no one would have predicted Covid and how that virus will change the way we work, travel, and use buildings. But other than that I would definitely choose my business partner more wisely, creating a business is not like a friendship or fun game, and anyone that is not committed 100% should not be an entrepreneur.
Right now I have a great co-founder that has experience in both working in large corporates and also in entrepreneurship and we are working 100% to make INESS one of the leading platforms in behavioral AI models for commercial buildings
What problem does your business solve?
We developed INESS in response to the challenges of energy efficiency in small-medium-sized commercial real estate. Small and medium-sized facilities are traditionally overlooked by big Building automation and management technology companies who specialize in large corporate customers. Small-medium-sized businesses have trouble making business cases for investing in expensive building automation systems and lack of human resources to operate and maintain those complex systems.
INESS improves operational efficiency in these buildings without needing to invest in expensive building automation systems by reducing lighting and AC usage based on human behavior and occupancy patterns as well as indoor circumstances.
What is the inspiration behind your business?
INESS was born out of the necessity to solve a problem that was affecting our everyday life; we wanted to improve the experience of communicating with the buildings, creating an intelligent operated building.
The biggest problem that we are facing comes from the small and medium-sized buildings below 100k ft2 that do not have any BMS or smart system installed in their building. There is a potential in small structures that could cut energy use from 27% to 59% through the deployment of adaptive data-driven building technologies.
Therefore we are focused on small-medium-sized business owners, building owners, and investors that can not afford to integrate expensive and difficult to use and maintain smart building or building management systems.
What is your magic sauce?
INESS is a behavioral occupancy analysis system for small-medium-sized commercial properties.
INESS converts commercial spaces into data streaming sources to model human behavior and how indoor circumstances affect that behavior by integrating the INESS system into the structure of the building.
The system developed predictive models on usage trends and indoor circumstances.
The models and data that is created through the INESS system are streamed into the data exchange platform where the data is sold for an ever-increasing number of vertical sectors such as Marketing, Consulting, Smart City Applications, Financial and Insurance Markets so that building owners can monetize their data and in the same time optimize their operations and investments.
What is the plan for the next 5 years? What do you want to achieve?
In the future, anyone would be able to buy data from commercial buildings. This data is the evolution of how companies are able to interact with modern business buildings.
Our plan is to create the first blockchain-based Building Data Exchange Platform BDex.
We offer a solution to the problem of buildings not being able to benefit from Big Data by converting them into data sources. We will enable the owners of commercial buildings to use their own data by taking a percentage for bulk sales or as an API reseller, while also allowing building owners to sell their data individually to each end-user specifically interested in their building.
Imagine the possibilities of knowing how much traffic is going on in your local shopping center, how many customers are in a nearby restaurant, or even what your building is doing right now. On BDex you can utilize commercial building data as if it was your own to make smart business decisions fast.
What is the biggest challenge you’ve faced so far?
As every startup, we are also facing the problem of connecting with investors that are interested in Deep-tech and longer vision than traditional tech investments. Of course, like every hardware + software company, we are still facing problems in the supply chain and especially in certain chips that have now over 15 weeks of lead time. To solve that problem we have partnered with one of the largest manufacturers in electronic sensor systems.
How do people get involved/buy into your vision?
We would like to develop strategic partnerships with companies that are interested in commercial building data. Companies working in Insurance, smart city projects, Energy Efficiency systems, HVAC and lighting systems services, and maintenance companies. We would like to develop a network with partners that can benefit from both the data that the INESS system is creating and also with the models that we develop from the data.