Data science services

Thanks to our experience in working with data and building ML models, we will design and create a solution suitable for your case. We will also help you integrate it with the existing code of your solution if necessary.

If you feel that your existing AI/ML solution does not meet your expectations for some reason, we can analyze it for you and give specific recommendations on how to improve it. We can also optimize it or modify it for you.

Time series forecasting means using historical, time-stamped data to enable accurate predictions. Our services include experimentation with various predictive models, which leads to the optimal one in terms of accuracy and execution time.

By constantly monitoring the consumption of network resources (e.g. link occupancy) and by using ML techniques to forecast this consumption in the future, any necessary network capacity upgrade can be made at the right time. A similar approach can be used in a data center to proactively increase CPU, memory and storage resources.

Alerts are usually triggered (within a monitoring application) when some event occurs, some condition is met, or the measured value of a certain metric exceeds a defined threshold. However, triggering an alarm does not necessarily lead directly to remedial actions. Using AI/ML techniques can filter out non-meaningful alarms and make alerting more intelligent.

Load balancing in a networking environment and lack of congested elements is the desired state for proper operation. Continuous observation of traffic flows’ bit rate and forecasting such time series in terms of trends and seasonalities using ML models allows for proactive and automatic routing reconfigurations. This way, you can achieve the desired load balancing on the links.