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Technology

State-of-the-art technologies are in the DF house. We are using the most advanced technologies today to come up with custom made solutions that make life running smooth and easy.

Technology

Big Data

Global digitalization brought us in the era where massive amounts of data increased exponentially in time. The biggest issue is that traditional data processing software cannot deal with this impact of extremely complex and large data sets. To overcome these problems, a combination of technologies such as machine learning, artificial intelligence, Internet of Things, augmented reality and a whole lot more are introduced as Big Data technologies.
Through Big Data technologies we can analyze, process and extract complex and massive amounts of data in real-time.

Not only that we are going to analyze, process and extract complex and large amounts of data, but we are going to use every aspect of every data to learn about our system and our processes, to enhance our business cycle, to predict and prevent possible faults, to react in real-time, create collective knowledge and much more.

Big Data Tech Stack:

Kafka, Flink, Spark, Kafkastreams, Hadoop, Solr, Elasticsearch, NiFi, Druid, influxDB, ClickHouse, Pulsar, MongoDB, Neo4J, Cassandra,

Big Data

Cloud

Connected world is the place where we live now. You want to be able to access all your resources, tools and applications from wherever you are. Thanks to the cloud technologies, this is possible. If you are a small company and you are buying monthly storage on Oracle, AWS or Azure, or you are a big enterprise and you want to build your own private cloud based on OpenStack, it is not a problem. We can support you to reach all your resources from the office or from the beach.

Flexibility is the main advantage of using. Work should not suffer if employees are prevented from coming into the office. Monitoring of the system can be done remotely, access to the needed files and tools. Cloud gives us the possibility not to spend 2 hours in traffic, but to use these 2 hours for effective work.

Cloud Tech stack:

OpenStack, Oracle Cloud, Microsoft Azure, AWS, Docker, Kubernetes, Ansible, Maven, Mezos, ConcourseCI, Mezos

Cloud

IoT

Enable your devices, robots, machines to communicate with you. We are digitizing your hardware equipment, so that you can easily monitor your resources and see if there are any anomalies and if everything is working fine.

Possible breakdown in a manufacturing chain can cause big problems regarding time to fix machines and loss because manufacturing chains must be stopped. With our monitoring IoT solutions we can predict if some of the machines will be broken in the near future. With this prediction users can react upfront and prevent unnecessary loss and further damages on equipment.

IoT tech stack:
  • -Virtual reality for 3d data representation
  • -WebGL: three.js, babylon.js, D3.js
  • -General web technologies: node.js, angular.js, react.js
  • -Monitoring tools: Kibana, Grafana
  • -Prometheus, Graphite
  • -Interactive analytics: Tableau
  • -JMX

IoT

Artificial Intelligence

Companies are in the phase where they want to have a more digitized and autonomous way of working. These wishes turned heads towards Artificial Intelligence. Faster, more accurate, deep analytics, learning methods are only some of the benefits that companies get with AI. Investments in AI technologies are raising on a daily basis and as today's world is changing rapidly companies who will not adapt and accept AI as a crucial part of their business will not be competitive on the market.

AI is the final goal, however before AI can make decisions on its own, humans need to train it over deep learning platforms. That means first we implement deep learning models as an interface for training and after a certain amount of trained data AI model will start helping you on its own.
AI brings advantages like autonomous root cause analysis, predictive analytics, anomaly detections, learning possibilities, error reduction, 24/7 availability and much more..

Artificial Intelligence tech stack:

Tensorflow, Theano, Keras, Scikit-learn, NLTK, PyTorch, Caffe2, custom-maid AI models, custom-maid ML models

Artificial Intelligence