MUNINN and the competition

Are you are looking to compare
3 quality vendors in the NTA space?

Or maybe you are looking for a more cost effective alternative to your existing solution – but high quality, strong and more than sufficient tool for full network traffic analysis with Machine Learning and AI – doing in-depth anomaly detection?

MUNINN does the job – it detects and stops the cyber threats of tomorrow – and at a fraction of the cost of the competitors. So we encourage you to let us have a true shot at proving we get the NTA job done well in your network.

Have you considered the following features? MUNINN supports them all:

  • Detect unknown threats and zero days in your network using AI and Machine Learning
  • Full, in-depth interaction analysis using Machine Learning to reveal insider threats and espionage
  • MUNINN Freki AutoPrevent isolates infected hardware in real-time
  • Full packet capture, protocol analysis and raw data analysis
  • Monitor in cloud or on premise devices
  • Detect commodity threat using known blacklist and indicators of compromise (IOC)
  • Detection of suspect behavioural traffic patterns
  • Full integration to SIEM / Log management tools, including flows
  • Full service solution possible including hardware and alert monitoring
  • Cloud monitoring and hybrid monitoring
  • Multi-tenancy for data centers (for hosting providers)

We have been validated against the major players in the market like Darktrace, StealthWatch, Vectra and ExtraHop.

Engage with us and let us show you how our technology stacks up against the competition in a free PoV.

Testimonials

Horten – a 400 user Danish law firm

“We were fascinated by how the artificial intelligence learns the normal behavior in the network, and how MUNINN detects and reports abnormal behavior and threats – furthermore at a cost effective price.”

MORTEN KAMPER MATHIASEN – Head of IT

Atlantic Airways

“We experience a greatly increased Cyber Security Response Readiness and early detection capability using MUNINN with its Machine Learning anomaly detection.”

HANUS – IT manager

DANX – a fast growing freight company

We needed to know what happened in our corporate network. Who do we communicate with and how? Also, we needed a technology which could support our GDPR compliance, which is another main reason for the implementation of MUNINN.

JAN LARSEN – IT manager