AI Network & Security Analytics

Every firewall, every server and every office network produces a log. Most small businesses never read that log. We apply AI-driven analytics to surface the signals that matter: a device that is suddenly talking to a known malicious IP, a user who is logging in at unusual hours, a server that is filling up faster than normal.

What we look for

• Unusual outbound traffic that suggests malware or data exfiltration.
• Failed login spikes that suggest a brute-force attempt.
• Configuration drift between firewalls across sites.
• Performance anomalies that predict a hardware failure before it happens.

How it works

We aggregate logs from your firewalls, servers and cloud services into a SIEM. The AI component reduces the volume of alerts so your team sees a short list of things that need a human, not a daily firehose of noise.

Why your firewall logs are full of noise

A busy office firewall logs thousands of events a day. Most of them are normal: a web request, an update check, a dropped connection from the internet. A small number are signals: a device talking to a known malicious IP, a user logging in at 3am from a country they have never visited, a server that is suddenly sending 10 times its normal outbound volume. Without analytics, those signals are buried in the noise.

What we surface

• Unusual outbound traffic that suggests malware or data exfiltration.
• Failed login spikes that suggest a brute-force attempt.
• Configuration drift between firewalls across sites.
• Performance anomalies that predict a hardware failure before it happens.
• Certificate and domain expiration that no one is tracking.

How we reduce the noise

We aggregate logs from firewalls, servers, cloud services and Microsoft 365 into a SIEM. The analytics component learns the normal pattern for your environment and alerts only on deviations. Your team receives a short list of things that need a human, not a daily firehose.

It surfaces the short list of anomalies that need a human, reducing the time between a problem starting and a person noticing it.