Self-learning :  required to succeed
with Digital Business
- Automatic anomaly alerts -
- Auto-discovery and enrollment of new applications -

Organizations are set up to fail with existing tooling

IT systems are getting more complex and the need to cover a broader set of infrastructure, applications and services across on premise data centers and cloud increases rapidly.  

The ability to use manual tasks and traditional threshold based alerting tools is outdated
and will drown you in manual tasks without a chance to succeed.

AIMS use Machine Learning and cloud computing to automate sophisticated anomaly based alerting covering a hundred times more scenarios than traditional solutions
- automatic and out-of-the-box.  

Further AIMS auto-detects new applications and
automatically include new applications into your monitoring.

Putting Machine Learning to work for business-critical systems

AIMS automatically build thousands to millions of patterns

for each customers to cover all possible scenario -

- and continuously monitor actual performance against
the patterns to identify deviations and anomalies.

See Anomalies to learn how AIMS use the deviations in anomaly alerts.

Machine Learning algorithms continuously learn the normal behavior for all metrics and algorithms identify critical anomalies in real time - enabling you to prevent instead of firefight. 

Customer benefits

Customer value: 

What if you could easily apply machine learning and AI to all performance data relevant for you critical systems and gain critical insight in real time?

We didn’t jump on AI and machine learning when it became The Next Big Thing™ – AI has been a part of the solution from the starting point, applying it to solve real-world problems. 

AIMS' modern IT monitoring solution leverage machine learning and AI to automate installation, configuration, insight and alerting while delivering time-to-value in hours and days - not weeks and months. 

We are proud to be vendor in the Artificial Intelligence space (AIOps) as defined by Gartner in 2017.