Alerting & Reporting

Exeon’s Smart Alerting: Focus on What Matters

Security teams face overwhelming alerts, causing missed threats and delays. Our risk-based alerting system filters noise, highlights critical incidents, and dramatically improves efficiency.
Cutting through the noise

Challenges of security teams today

of organizations cite complex and evolving threats as their biggest challenge to cyber resilience.

0 in 3

of businesses experience Advanced Persistent Threats, yet only 30% have real-time detection capabilities.

0 %

is the amount of time spent by victims of a cybersecurity attack to determine the security measures they need.

2 + hours

Security staff need highly flexible whitelisting methods to achieve sharpened alerting accuracy and define trusted users, devices, and processes to minimize unnecessary alerts.

Custom whitelist rules

Identify the expected, known behavior of trusted users, IPs, service accounts, devices or processes to filter out safe traffic so analysts aren’t swamped.

Adaptive learning

AI models monitor ongoing behavior and automatically prevent alerts from even being raised for patterns that are repeatedly confirmed as benign.

User-centric controls

Granular policy scopes (per function/network/criticality) let security staff whitelist on CMDB information retrieved from asset databases and tune detection sensitivity to match the organization’s risk appetite.

Solution

Smarter alerts, faster responses

Dynamic risk scoring
Machine learning models display every alert based on events and their according scores, so analysts can tackle the most dangerous issues.
Contextual threat analysis
Metadata enrichment adds user, asset and location context to each event, slashing false positives and telling you why it’s risky.
Automated incident correlation
Related alerts are stitched into a single storyline, giving you a 360° view of the attack and cutting investigation time to minutes.
Adaptive AI models
Behavior profiles stay up to date on your network’s norms, evolving with new workloads and keeping detection accuracy high, without manual tuning.

Empowering security teams worldwide

Steps to cut through the noise

How you’ll achieve an advanced alerting system with Exeon

AI-driven analytics

Exeon’s behavioral ML inspects every flow in real-time, spotting subtle variances that signal emerging threats, to get early warnings before an anomaly becomes an incident.

Optimize whitelists

Define or import trusted users, devices and processes; the platform suppresses their routine traffic automatically—noise drops, analysts focus on true risk.

Enhance detection with behavioral analytics

Continuous user and entity-behavior analytics expose insider abuse, credential theft and account takeovers, so that hidden, context-based threats come to light.

Integrate SIEM & SOAR with automation

Exeon feeds risk-scored alerts to your SIEM/SOAR stack, triggering playbooks that quarantine hosts and collect forensics in seconds, for faster response, cleaner investigations and zero manual toil.

Use cases

Exeon in action

AI-driven security in action—download our use cases risk-based alerting and enhancing threat detection and response.
CVSS Guide - Exeon

How AI benefits threat triage

Here’s how security teams increase precision by using AI-empowered vulnerability scoring.

Less false positives with AI

Save time and focus your efforts on what matters most with AI-supported alerting.
APT threat detection demo tour

Guided threat detection tour

A video demonstration of exeon.NDR including domain generation algorithms, machine learning for behavioral analysis, lateral movement, and much more.
How to detect APTs - Exeon Analytics

AI against advanced threats

A comprehensive guide on the current threat landscape, and precisely how to improve detection and response capabilities.

Trusted by leaders

Exeon.NDR streamlines alerting and reporting to ease security teams workload and are used by organizations worldwide.
Additional solutions powered by Exeon.NDR
Exeon.NDR-powered solutions

Further solutions

Industry use cases

Industry-tailored, threat-focused

Banking & finance

Use Case: Bank in Germany

DORA compliance, tackling threats like APTs & ransomware, improved threat detection, and faster response times.

Logistics & transportation

Success Story: Logistics

Fast-moving, international logistics company defeats system interruptions from cyber incidents with Exeon.NDR.

Banking & finance

Success Story: Banking

A cybersecurity case study on PostFinance, one of Switzerland’s leading retail financial institutions.

Manufacturing

Use Case: Manufacturing & NIS2

OT/IIoT integration and compliance: how a mechanical engineering company increases their cybersecurity posture.

Healthcare

Success Story: Swiss Hospitals

Read how our platform became an integral security monitoring tool to safeguard Solothurner Spitäler’s IT & OT networks.

WinGD customer use case
Manufacturing

Global Manufacturer WinGD

In this video testimonial, our customer WinGD explains how Exeon.NDR strengthens their cybersecurity.

FAQs

Frequently asked questions

Exeon’s smart alerting helps security teams cut through the noise of overwhelming alerts, ensuring they focus only on what matters. By prioritizing critical security incidents with a risk-based system, it boosts operational efficiency and enables faster, more effective responses.
How does Exeon’s smart alerting system improve security operations?
Exeon’s risk-based alerting system prioritizes high-severity incidents while filtering out low-risk or benign activities. This allows security teams to focus on real threats and significantly reduces noise, improving response time and operational efficiency.
Whitelisting helps organizations eliminate unnecessary alerts by allowing security teams to define trusted users, devices, and processes. Exeon’s approach includes custom whitelist rules where organizations can create policies that exclude known safe activities, adaptive learning where AI continuously evolves, recognizing benign patterns to prevent redundant alerts, and user-centric controls where security teams maintain full control over whitelist configurations to align with organizational needs.
Exeon’s machine learning model ranks alerts based on severity, ensuring that critical threats receive immediate attention while low-priority issues do not consume valuable resources. A how-to guide for vulnerability scoring and risk-based alerting can be found on our downloads webpage.
Contextual threat analysis enriches metadata to provide more accurate detection. By understanding the full context of network activity, Exeon can distinguish between normal behavior and suspicious anomalies, reducing false-positive alerts.
Instead of treating alerts in isolation, Exeon’s AI connects related alerts, providing security teams with comprehensive visibility into ongoing security incidents. This enables faster threat identification and response.
Exeon’s adaptive AI model learns from past incidents and refines detection mechanisms over time. By continuously developing its understanding of network behavior, the system improves its ability to detect complex, emerging threats and insider risks.
This can be set as required; some customers keep the alerts for 3 or 5 years. As the alerts are stored separately, this is independent of the retention time of the log data. For example, at least 3 years would make sense.

Talk to an expert

Our platform is designed so you can act fast when it matters most. Ready to experience AI-driven alerting and enhance operational efficiency?