Network Detection & Response Built for AI-Driven Attacks

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Adaptive ML vs. Pre-Trained ML

Most security tools rely on pre-trained machine learning models or static rules that can only recognize what they’ve already seen. Cyntros AI is different. It uses adaptive machine learning that learns directly from live network traffic and reshapes its understanding continuously to:

  • Surface both existing and novel threats. 
  • Discover attackers targeting unknown vulnerabilities. 
  • Stop new attack methods in their tracks, like zero day attacks.

How It Works

Data Ingestion

Behavioral Modeling

Alerting & Visualization

Detects what other tools miss

Works Out of the Box

Fits Into Your Stack

Transparent Pricing

Change How You Understand
Your Network

Questions? We’ve Got Answers.

What is Adaptive Machine Learning (AML), and why does it matter for Network Detection and Response (NDR)?

AML is a form of machine learning that adapts to your network and updates itself  from live data instead of being trained once and then frozen. On the network, that matters because AI-driven attacks now arrive faster than anyone can update a model, while signatures and static rules only recognize what they have already seen. Cyntros AI learns directly from your network traffic and keeps reshaping what it knows, so it can spot the threats security teams already know and brand new ones too, including zero day attacks a signature list would never flag.

Does Cyntros AI work across cloud, on-prem, and hybrid environments?

Yes. Cyntros AI is an NDR platform that can ingest network information from a variety of sources, including TAP/SPAN ports, cloud traffic mirroring and flow logs to support cloud, on-prem, and hybrid implementations.

What security tools does Cyntros AI integrate with?

Cyntros AI integrates with SIEM, XDR, and SOAR platforms, and it can send real-time alerts and visual context to where your team already works, including Slack, Teams, and SMS. It fits into your existing workflows rather than replacing them, so adding it does not mean a rip and replace of your current stack.

How does Cyntros AI build a baseline of normal network behavior?

Cyntros AI studies how your systems normally talk to each other and what typical traffic looks like, then turns that into a live baseline. The baseline keeps adjusting as your environment changes, so it stays accurate over time. When something breaks from the pattern, Cyntros AI flags it on the spot, which is how it catches attacks that predefined rules never account for.

How soon does Cyntros AI start detecting threats after deployment?