AI cybersecurity for adaptive threat detection

Client

Netviss

Netviss is an AI-powered cybersecurity platform for adaptive threat detection, network visibility, and security operations — signal over noise for teams drowning in alerts.

Project

Tasks

• Ingest firewall, endpoint, and cloud logs into a unified timeline
• Surface ranked incidents with natural language summaries
• Integrate with existing ticketing without replacing SIEM
• Dashboards for security operations leadership

KPIs

1. 1. Faster triage — median time to first actionable insight
2. 2. Lower false positives — ranked queue vs. raw alert flood
3. 3. Analyst adoption — daily active use within first month

Project journey

1. 1. Data foundation

   Normalized schemas and retention policies for SOC search.

2. 2. AI sprint

   Ranked anomaly detection evaluated on historical incidents.

3. 3. SOC integration

   Ranked incident UI embedded in analyst workflow.

Challenges

SOC analysts faced alert floods with low signal. Without ranked incidents and explainable context, triage time ballooned and true threats competed with noise.

• Alert fatigue buried real incidents under high volumes of low-value noise.
• Slow triage forced analysts to reconstruct context across tools before acting.
• Weak explainability made it hard to trust automated rankings without analyst-friendly summaries.
• Tool sprawl left detection and ticketing loosely connected.

Results