Kineticai Automation

Automate & Optimize

“Automation is transforming the business landscape. Companies are becoming more efficient, informed, and secure.”

- Gjergj Camaj | CEO and Co-Founder of KineticAI



AI helps manufactures maintain a competitive edge by improving the way they do business.

Supply Chain

AI helps businesses predict how resources should be used across an ever-growing number of internal and external sources.


AI helps the agriculture industry track and predict various factors which can lead to an increase in yields.

Be Efficient


Do more with less effort. Our intelligent automation solutions can help your business make faster decisions, reduce costs, and remain competitive. Allow your workforce to focus on scaling your business, not filling excel sheets.

Take control


Complexity redefined. Lost in a sea of data? Our technology can provide insights to help you identify trends, make better predictions, and improve customer retention. Reduce complex data into easily digestible chunks of useful information.

Stay Secure


Humans are not machines, and that’s okay! Minimize human error by automating their tasks. Protect your business by using machine learning to identify and issues while your workforce is asleep. 


The manufacturing sector is facing significant changes due to rapid technological development. The sector is being forced to work smarter and operate more efficiently in order to remain competitive. The ability to compete can be maintained by identifying areas in need of improvement. Smart manufactuers with a data-driven edge are taking the lead. They are using sensors to gather latent data, collaborative robots to improve efficiency, and AI to transform information into actionable steps.

Automation helps manufactures maintain a competitive edge. Smart manufacturers automate parts of their workforce by using AI in conjunction with robotics. Extend the longevity of your equipment by using predictive maintenance capabilities to monitor asset conditions and suggest inspections before there is a critical issue. Utilize AI-powered quality controls to minimize defects, increase output, and identify bottlenecks.


The labor-heavy agriculture industry is susceptible to a variety of environmental factors. These factors are hard to quantify and predict. New technologies are paving the way for improved risk management, automation, and efficiency. These new methods are helping the industry produce better yields and reduce labor costs. 

AI helps the agriculture industry track and predict various factors, such as weather or the spread of disease, on crop yields by using predictive analytics. Through the use of sensor data and AI, farmers can be provided with valuable insights regarding their soil, crops, and machines. This information can be used in conjunction with agricultural robots, to harvest crops at an optimal time and at a lesser cost than a human works force.

Supply Chain.

The rise of data volume and data complexity has impacted the way businesses manage their supply chain. What was once a linear supply chain path, is now a set of dynamic integrated networks, characterized by a continuous flow of information and analytics.  Companies are adapting a streamlined approach for supply chain management by using technology. 

AI helps businesses predict how resources should be used across an ever-growing number of internal and external sources. Through the use of cognitive and concurrent planning, businesses are provided with actionable insights that are improving efficiencies across their supply chains. Machine learning is being using to provide information on adjacent possibilities. AI can be used to understand the interconnected nature of sensor data, distribution, transportation, manufacturing, marketing, and sales.  

Get To The Next Level With AI

Industrial Automation Products

Computer Vision

Computer vision analyzes and interprets any form of visual-based input. It can be used for object, scene reconstruction, object tracking, and optical flow.

Deep Learning

Deep Learning, a subset of machine learning, uses artificial neural networks to adapt and learn from large datasets. It can be used for classification, extraction, forecasting, speech recognition, text recognition, and anomaly detection.

Natural Language Processing

NLP enables contextual understanding of natural language. It can be used to automatically extract critical insights from copious amounts of structured and unstructured content.

Intelligent Agents & Chatbots

Intelligent agents automate routine tasks that take time away from other value-added activities. It can be used for customer interaction (chatbots), employee training and assistance, and customer service.

Machine Learning

Machine learning algorithms have the ability to learn without especially being programed. This field is being used to automate processes across industries. It can be used for patient diagnosis, fraud detection, inventory optimization, demand forecasting, intrusion detection, and research insights.

Generative Adversarial Networks

GANs utilize two neural nets that are in competition with one another. This method generates a variety of content automatically. It is used to produce computer generated graphics, realistic speech, increased image resolution, and image-to-image translation.

3D Vision

Create a real-time 3D area map of an environment. Artificial intelligences takes SLAM to the next level. This is used in augmented reality, self-driving cars, virtual reality, and UAVs.

Machine Automation

Machine automation is any information technology that is designed to control the work of machines. AI can be used in conjunction with machines to improve efficiency and increase autonomy.

Predictive Analytics

Predictive analytics includes a variety of statistical techniques from data mining, predictive modelling, and machine learning, that analyze current and historical facts to make predictions about future trends.

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