About Us

We are an AI-driven organization based in The Netherlands Amsterdam area, which promotes the use of linked open data platform(s) and Deep/Machine Learning solutions for smart home/office automation using Internet-of-Thing appliances that support programmatic/API controls. We provide top-of-the-line products & services packaged & customized to augment & integrate data streams in home/office context to make Internet-of-Things appliances&virtual assistants smarter through applied technologies from Artificial Intelligence, Machine Learning, Linked Open Big Data Science & Semantic Web. We provide Data Science & AI Solutions for recommenders, chatbots & digital assistants to acquire, integrate&combine knowledge from Internet-of-Things&Semantic Web repositories using Data Science pipelines, Machine Learning algorithms & models, to focus on smart applications like Object Recognition&Classification, Scene Understanding, Emotion Recognition&Content Summarization in Text&Multimedia content. Live with us our vision for Digital AI-enhanced Home/Office Ecosystem.

How it works? Instructables/NewsletterYou sign up with your email or SMS, city and usage scenario of interest, and we respond by e-mail with products & services are available in your area. If you opt-in for our newsletter, you get weekly top 10 package improvements for home/office automation. Products You get a hand-picked cost, efficiency & energy-efficient package of smart appliances, including sensors, actuators and IoT hubs/edge devices for your specific smart home/office scenario of interest. Services Our main added value is an assistant mobile/web app & appliance to control & customize the "brains" of your home/office on a local server (isolated from internet) or, if you so prefer, in a fully secured cloud. You have one week to one month to customize the package and try out the software and to decide whether you would like to rent or buy it, further customize it, or you want to stop using it altogether. You can stop at any time your subscription and return any rented products within the prepaid subscription costs. We are dedicated to protect your privacy & guarantee the safety of your sensitive data stored within our platform. Our data appliance software & hardware is periodically tested against data leaks and/or unwanted access. For cloud-connected appliances, you can opt in to participate in a device hunt to collectively harden the security of the platform. You make reversible steps, no unwarranted risks for your data or unnecessary up-front investments & hidden costs. You can choose between prepaid subscriptions or pay only for what you use. For an affordable subscription fee (ranging from 10 up to 20 EUR / month), we help you make use of and keep our supported devices up-to-date in a safe, smart & comfortable way. On request, we provide fast & responsible delivery, collection or transfer of ownership of consumables, data, instructables, software/models and services for the supported appliances. Note:We are still growing our business. We provide the products & advisory services across the world, but some rental, logistics, repair & delivery functions are for now only available within EU/Europe, until we have arrangements with an organization in your area.

About Me

I'm a Freelance Data Scientist, AI MLOps/DevOps, Solution Architect & incidental blogger on full-stack AI solutions, i.e. content augmentation & multi-modal interaction & task optimization within hybrid teams (people, devices & bots) using video, speech, gesture, text & sensor signals and applying best practices, models, algorithms & methods from Deep Learning/Machine Learning/Big Data/Edge-Fog-Cloud applied to Internet-of-Things. In recent past I have contributed to several enterprise IoT solutions for video situation understanding, language understanding and signal analytics from multimedia event streams and their integration with Data Science pipelines and Machine Learning models deployed in production. I published academic papers on linguistic patterns recognition in texts for automated tagging, text-to-model guideline operationalization & model building & critiquing, and ad-hoc decentralized resource optimization for task coordination in distributed teams. I am passionate about extracting new insights from datasets and investigating how zero-shot learning, incremental learning and federated learning can take place with private and virtualized data sets, for instance data store in a knowledge graph structure like the one in a blockchain or in a social network. I have full stack development experience including building cross platform applications and services.