DataFlux Observability

DataFlux Observability

Enables you to cut costs and to speed up your business

Observability - active monitoring, collective knowledge and real time problem solver.

Any anomaly or malfunction that is happening in your system and giving you a headache, we can track and find a root cause of the issue in real-time. When the root cause of the issue is found, domain experts will provide the solution and train AI models with their knowledge (collective knowledge). After our AI models have learned enough information about your system, they will be able to fix old and new issues on their own. DataFlux Observability solution is modular, which means we can adapt it to the client needs in a no time and deliver custom maid solutions for each customer.

Collective Knowledge for a superior system performance


Automation of problem finding and problem solving


Faster reaction, problem solved quicker with less or no impact on services


Collective knowledge, the main strength of any company is knowledge and this stays in the company


Lower costs for running
the system

Autonomic for smooth dynamic

Observability platform is a modular solution which gives us the possibility to customize the solution just right for your needs.
Modules like deep analytics, aRCA, self-healing, predictive maintenance and Machine Learning/Artificial Intelligence enable us to provide you with everything that you need for autonomic and smooth running of your business.

Deep Analytics

Problem tracker

DataFlux system is data agnostic which means it will process everything from structured to unstructured data types, such as metrics, logs, KPIs, alarms, network packets and much more. Through this system, users can deep dive in the data analytics on several layers and represent them in different views, such as graphs, charts, tables and heat maps.

Deep Analytics

Autonomic Root
Cause Analysis

aRCA – Problem finder

By actively observing the complete network, we can detect a problem in a fraction of a second. We can also detect where the problem occurs, yet we can determine the direct cause of the problem. After the root cause of the problem is detected, a domain expert who is responsible for the specific area can solve the problem in a matter of seconds/minutes.

Autonomic Root Cause Analysis

Machine Learning

Machine Learning

Machine Learning (AI) is our secret ingredient that runs and enhances all the processes in the DataFlux platform.
Machine Learning model – all events that bring specific error messages are correlated and classified as an incident by a human expert.
DataFlux ML model collects all entered data and learns about correlated events and classified incidents.
Artificial Intelligence model – learned data are collected and used for training of our Artificial Intelligence model. The more data AI model consumes, better it will be in decision making when new problems occur.

Machine Learning


Problem Solver

After DataFlux has learned a huge amount of data about events and incidents, it will be able to handle old and new incidents. The system will detect, correlate and solve the incident on its own. Every new incident will be cross-checked with incidents from the past and if the new incident is not in the database, the Artificial Intelligence model will analyze new events and offer the best possible solutions for the incident.

Predictive maintenance

Prevent the problem

Infrastructure – by actively monitoring complete network infrastructure our AI models will detect any oscillation of the normal behavior and it will treat it as an anomaly. If these anomalies start to appear regularly, DataFlux will give predictions until the infrastructure is able to function without service impact.

Data – predictive analytics. DataFlux will detect if there is an unusual amount of traffic in an observed system or if the data is corrupted. In the first moment of detection, corrective actions will be performed, to stop further data damage.

How we do it

Collect data

Collect data

  • Logs, Network packets, Events, Alarms, Metrics, KPIs
Real-time stream processing

Real-time stream processing

  • Log/Event analysis: Statistical and machine intelligence supported log processing. Anomaly detection, irregularity, etc
  • Network analysis: Processing of network packets: packet flow analysis, correctness of packet contents, security aspects of network traffic
  • Metric Analysis: Anomaly detection on time series data: metrics, key performance indicators, performance measurements
  • Correlation: Events, alarms and anomalies from different processor units are correlated to improve whole picture about the problem
  • aRCA: Autonomic root cause analysis with hybrid approach: machine learning paradigm combined with knowledge modelling in dependency graphs
Machine Learning/Artificial Intelligence

Machine Learning/Artificial Intelligence

DataFlux own developed AI models for:

  • Anomaly detection
  • Predictive intelligence
  • Autonomic root cause analysis
  • Fingerprinting (learning)
  • Correlation


  • Data storage in persistent databases and analytic systems
Visualization/ Human-AI collaboration

Visualization/ Human-AI collaboration

  • Real-time data visualization and historical overview
  • Interactive Analytics

Let our artificial intelligence
models work for you.