AI Santinels for your Business

The level of security breaches and attacks is at an all time high, with analysts having to deal with thousands of security alerts daily.

An important aspect in managing the flow of alerts is triaging them to identify the ones which are critical and require further investigation.

A process which is now done manually.

The pressure that security teams are under to keep businesses secure leads to fatigue and a workforce deficit due to analysts changing jobs or leaving the organization. Unfortunately, when this happens, analysts take their knowledge and experience with them and onboarding new analysts takes time in bringing them up to speed on organization specifics.


Security teams deal on average with 11,000 alerts daily:

0 %
are manually reviewed
0 %
are false positive
0 %
are ignored
0 %
are touched by automation


Cognitive Automation platform that focuses on addressing the alert triage challenges by combining deep learning, automation and user feedback.

This unique mix of capabilities enables Arcanna to analyze, learn from expert knowledge and automate the decision-making process for alert triage.

For organizations, this translates into more time for security experts to focus on hunting, investigating  and responding to real threats without being burdened by false positives or irrelevant alerts.

Through feedback, the expert knowledge is captured and encapsulated within the deep learning model assuring that when a decision is made, the knowledge and experience of all your analysts is used.


Integrations seamlessly integrates within your existing ecosystem, connecting to a multitude of out-of-the-box solutions and custom-built applications through custom connectors.

Integrations are a vital component that enables process streamlining through data collection, processing, automated decision making and post-decision automation.

AI Jobs

The bread and butter of, AI jobs, represent streams of data processed through the deep learning model to automate alert triage. As alerts are processed, each alert is analyzed by the model and decides if that particular alert should be dropped, is a duplicate or it should be escalated. During this analysis process the knowledge collected by the model from user feedback is applied to each alert, ensuring that all alerts are treated with the utmost importance.

Knowledge & Experience Capture

Intuitive, no-code model training through the use of the UI. Your security experts can provide feedback to the decisions of enabling the model to learn from the collective knowledge and experience of all your analysts while also adapting to the particularities of your organization.

Model training

As feedback is collected the model can be retrained to encapsulate the newly gained knowledge into the automated decision-making process. Through model versioning you can choose whether you want to use your current model or revert to a previous one

Post-decision Automation

Once a decision has been taken by, it can be integrated with post-decision tools such as collaboration and messaging tools, incident response platforms or automation tools to further streamline operational processes with smart decision making


Improve incident response time

Enable analysts to focus on real threats rather than identifying them by taking the manual work of triaging thousands of alerts daily.

No-code model training

Train your own deep learning model that learns from security experts’ knowledge and experience and adapts to your organization’s particularities without writing a single line of code.

Expert knowledge capture

Collect and consolidate the knowledge of your experts within a deep learning model that addresses all alerts with the collective wisdom of your team.

Reduce alert fatigue

Eliminate stress and reduce the number of mistakes caused by manual repetitive tasks by automating the alert triage decision process.

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