Why gamble with your data?

Our machine learning and Dev team has helped 20+ top companies solve critical business problems with practical  digital twins and machine learning solutions.  Kagera provides made-for-you machine learning and digitial twins solutions to give you a competitive edge in the energy industry.


Machine learning isn’t a replacement for humans. It automates analytical tasks to help your team make data-informed decision faster.


New tools don’t need to disrupt your workflow. Our team builds solutions that fit seamlessly into your processes to speed up discovery and optimize development timelines.


You won’t solve complex challenges with pre-built tools. We work alongside you to develop one-of-a-kind solutions to your problem, building on your team’s domain knowledge.


Our Solutions & Services

 Kagera is more than consultants—we’re a team of developers, Business Analysts, Data Scientists, and Engineers. We build fully innovative solutions and we don’t rest until your solution is live and implemented in your business.

Some of our clients


Great effort and highly performance during project execution and looking forward to more cooperation with them. 

Mohamed Sammy

Manager of Projects Exxon Mobil Egypt, Petrosafe

We are truly moved by level of innovation Kagera AI and Optimize introduce in our company HSE project.

Eng Ehab Zeki

Technical Department Petrojet, SUEZ Projects, Petrojet

We want long term cooperation with you.


Head of Engineering for Petramina Projects, Indoenergy, Indonesia

Manja and her company Kagera.AI has worked with us on a strategic project of our gigantic field Geisum to perform & deliver machine learning solutions with objective of defining the risk on human, asset, and environment. Her tool of PyRISK has saved 66% of our allotted time and hence the cost to deliver a complete HSE case to EGPC (Egyptian General Petroleum Company). Her work has received an appreciation and high recognition from EGPC as the first study of its kind to be seen in Egypt.
On another front, Manja has helped us to make many financial decisions via the use of PyHAZOP and we almost saved an additional cost perceived from some scenarios. Her application of PyHAZOP and its dynamic features has helped us to nail down all financial decisions to proceed forward.
I do recommend PyHAZOP & PyRISK for all my connections and operating companies who are interested in applying and evaluating machine learning in process safety field.
Mohammed ElHager

Process AGM Manager, Petrogulf Misr



We’ve refined our process over the  16+ successful practical workshops to get our clients ready for digitiliaztion and AI implementantion

Upstream and GOSP (Gas Oil Separation Plant)

Our workshops where  Engineers and/or Management learn how to use disruptive technologies to exponentially boost their company’s success.


From Data analytics, Business Intelligence, Machine Learning, Deep Learning, Big Data, Dynamic Modelling

Gas Process and NGL

Based on our wide experience in oil & gas industry and delivering similar energy management roadmaps for MEA (Middle East and Africa) customer, we help  to DEFINE, DISCOVER and DELIVER a complete solution can fit the business needs. This workshop can conclude eventually a list of opportunities and business challenges to be further assessed to improve the Energy Consumption, increase the uptime, and increase the profit margin.


Our Methodology to not gamble with your money

Successfully implementing  digitial twins, machine learning, Artificial Intelligence in Energy business requires both expertise in data engineering and domain knowledge. Most often management teams think they can implement best practices for data analytics by directly adopting advanced technologies, such as machine learning (ML) — which leads to failure.

1. Prevent

Enterprises are focusing on innovation to stay competitive by driving digital transformation: the adoption of digital technologies to reinvent business processes and customer experiences to achieve more agility and improved KPIs. 

• Scalable data service to expose all data.

• Centralized policy-based governance and security infrastructure.

• Effective methods to gather all the metadata and make it discoverable.

• Kubernetes and the cloud for elastic disposition of resources.

2. Predict the downtime

A McKinsey study shows that diverse teams achieve better outcomes than homogenous ones. Companies that embrace diversity have a 33% greater probability of achieving above-average returns.

Tech and data science have historically been homogeneous industries. This is a problem when data scientists only represent one way of thinking, so they are likely to bring those unintended biases into the collection of data and algorithms used in applications. In addition, it’s a possibility that collected data already represents bias that was applied even before software and algorithms were involved. Simply put, if the data you are using has biases baked in, the machine will learn these same biases.

3.Optimize the production

Our team develops effective tools which smoothly cooperate with the existing software. We build our solutions based on innovative technologies like machine learning and big data.

Contact Us



2 Kraljice Marije Street, Belgrade, SRB

Monday-Friday: 9am - 5pm CET

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