5 key trends are changing the manufacturing landscape

…and Keepler can accompany you in all of them!


Industry 4.0 continues the push towards automation, employing technologies such as IIoT (industrial internet of things), big data, machine learning, artificial intelligence (AI) and advanced analytics.

AI for decision making

Predictive Maintenance and Digital Twin Technologies reduce errors. IIoT, combined with big data analytics, makes it possible to use sophisticated algorithms to predict these failures with high accuracy, before they occur.

Predictive Maintenance

Industry 4.0 continues the push towards automation, employing technologies such as IIoT (industrial internet of things), big data, machine learning, artificial intelligence (AI) and advanced analytics.

AI for processes optimization

AI in the supply chain is helping to deliver the powerful optimization capabilities required enable higher speed in decision-making, reducing cycle-times, operations, and continuous improvement.


The pandemic has led to the rise of the microfactory — small, highly modular setups that make use of leading-edge technology like artificial intelligence, robotics, and big data, to enable hyper-autonomous manufacturing.

Huge volume of data grows exponentially due to sensorization and needs to be analyzed in real time or near real time.
The challenge is collecting the “right” data and processing it for further analysis and exploitation.

Sensors on production lines, locators on vehicles, or even individual packages and handheld scanners in the warehouse are collecting data that must be stored, processed, and then analyzed.

The foundation for every modern analytics program is a cloud data platform where data of all types can be ingested and processed at any speed and delivered to users and systems alike in a manageable, scalable and effective way.

But, where does all that data go?

How do you pull all the relevant data together so you can use it to help make business decisions?

Industry 4.0 technologies are changing factories operations

We accompany you in the creation of a journey for the operational transformation of your industry

IoT Analysis

Integrate sensor data with structured data and obtain insights related to the operations, energy consumption, temperature, etc.

Event Data Lake

Capture events interchanged in the manufacturing plant that can be correlated with other system of the company.

Data Laboratories

On-demand data Science environments with data provisioned on-the-fly to data scientists.

Audio Analytics

Use audio analysis to detect abnormal operational situations.


Use automatic document management and text recognition to orchestrate automated processes using AI

Demand Forecasting

ML model analyze historical data to understand the demand, supply, and inventory, then forecasts the future demand, supply, and inventory

Video Analytics

Analyze video and images to extract insights related to customer identity, security, object recognition, garbage bins status, etc.

Anomaly Detection

ML model to identify data points in dataset that don’t fit the normal patterns.


Variables analysis to identify model for optimal performance conditions for ensuring a more efficient process.

Predictive Maintenance

Detect anomalies by analyzing data and predict future industrial equipment failures before they happen based on a ML model.

We help our clients transform their business through data

“Hand in hand with Keepler we managed to make a differential leap in our IoT project in the public cloud. It is the ideal partner because of its technological knowledge of the cloud and its methodological approach to data projects. In this world, where it is increasingly necessary to have a continuously updated expert knowledge and where talent management is so complicated, Keepler has been the best traveling companion to make our platform a scalable, reliable and secure product.”

- Head of Data Analytics & Engineering, Manufacturing Company -

Personal Protective Equipment Detection Using Video Analytic

Workplaces as refineries are places where workers must wear specific security material. It is hard to detect when workers are not wearing this material.

Big Data
Data Science

Plastic Bottles Manufacturing Quality Data Exploration

Identification and study of the variables that impact in the quality of the bottles manufactured so those variables can be managed to reduce the ratio of bottles rejected.

Data Science

Demand Forecasting

Our client carries out the demand forecasting process with a market solution. The development of new references and channels and the acquisition of new companies in the group have impacted the accuracy of the models (worsening) and the time spent in the process (one week per month).

Thinking about the future?

These are the goals manufacturing companies should strive for

Taking full advantage of new technologies for balancing customer satisfaction and cost efficiency

Ensuring effective execution of manufacturing operations and improving production efficiency through automation

Improving both operational and decision-making processes through Industry 4.0 technologies

Would you like to talk about your business?

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