We develop software and hardware industrial IoT products using cutting edge technology to solve common problems in manufacturing operations and logistics.
Fitbit and Strava in one for your factory. Evaluate your production effectiveness (OEE) and losses in real time without CAPEX and lengthy deployment. Easily verify the source of losses in retrospect from camera streams.
Product tracker for chaotic warehouses in heavy industry. Know the exact location of your products using our automatic tracking system based on computer vision and AI.
Cycle time computation
Compute the standard cycle time for any product just by observing the machine in operation and without burdensome retrofitting of the machine.
Get the OEE in real time and hence understand the margin of every manufactured product.
Logging invisible losses
No more paper logging by operators. Record automatically every single loss on your production machine, not only those longer than 5 min.
Know the exact position of every product in your warehouse. Learn how much time it spends there before shipping. No more need to deploy a workforce to search for the product.
How it works
Get the product
2. We come and install our device in 2 hours
3. We calibrate the system remotely in 2 hours
4. You monitor the OEE, plan, check, act and reap the benefits
5. You pay on monthly basis
PhD in chemical modelling, 4 years in management consulting focusing on manufacturing operations
Boris worked for four years as a consultant in McKinsey&Company. He helped to develop bottom-up and implement operations improvement initiatives at over 25 manufacturing plants across several industries and regions, with total EBITDA impact of the initiatives exceeding 1B EUR p.a. His eight years of prior academic experience helped him develop several rigorous analytical approaches to reductions of equipment utilization (OEE) losses, such as shiftly and weekly target setting based on distribution of mean time between failures. Low maturity of present tools for digital performance management available on the global market led Boris to quit consulting career and start InovecTech with the mission to bring latest academic research from machine vision and artificial intelligence to improve equipment effectiveness. Boris holds a PhD in mathematical modeling of rare events from the Univeristy of Cambridge, MSc in mathematical modeling of bio- and nanostructures from the Charles University and MEng in chemical engineering from the University of Chemistry and Technology.
Pavel has four years of industrial experience in product and technology R&D ranging from proof of concept to transfer to manufacturing. Previously he worked at BTL Medical Technologies and at TTP, a technology consultancy at Cambridge. He is a generalist engineer with experience across a wide range of technical areas from design and tolerance analysis of a switching mechanisms for mass manufacture to prototyping a magnetic field based displacement sensor or automating image analysis of aerosol speed. Pavel graduated with MEng from the University of Cambridge.
Peter worked the last two years for the Slovak government assessing major investments into road infrastructure and building transport models to describe current and future traffic flows in the country, a task involving processing and analyzing data from large-scale government databases. Before this, he pursued a PhD at the University of Cambridge in computational modelling of hydrogen fuel cells and improving current computational methods to describe a broader range of industrially-relevant materials.
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