ETT and Check Point
Technology we implement
ETT deploys Check Point as part of the secure-by-design network foundations underneath AI platforms — controlling the traffic, segmentation and threat prevention around systems that handle sensitive data.
Check Point is a technology ETT designs with, deploys and supports. No formal partnership is claimed, and Check Point is not an ETT customer.
About Check Point
Check Point Software Technologies is one of the longest-established names in cybersecurity, protecting networks, cloud environments, endpoints and users for over three decades.
Its Infinity architecture delivers consolidated threat prevention across the enterprise perimeter and beyond, backed by global threat research.
How Check Point fits into how we work
AI systems do not sit in isolation. They talk to data stores, APIs and each other, and every one of those connections is a path that has to be controlled. Check Point fits the ETT story as the network foundation beneath AI platforms, governing how traffic moves around the systems that handle a client's most sensitive information.
ETT uses Check Point to make secure-by-design real at the network layer. Rather than leaving an AI deployment exposed on a flat, over-trusting network, we segment and protect the environment so that even if something goes wrong, the blast radius is contained. It is unglamorous, foundational work, and it is exactly the kind of diligence that lets a client adopt AI in regulated, high-stakes settings with confidence.
Our work around Check Point
We account for existing network controls when designing the integration and data boundaries of an AI workflow.
Control the connections
We use Check Point to govern the traffic flowing to and from AI systems, so sensitive data only moves where it should and nothing reaches a model that has no business doing so.
Segment to contain risk
By segmenting the environments AI runs in, we limit how far any single compromise can spread, keeping a problem in one place from becoming a problem everywhere.
Foundations for regulated adoption
Consolidated threat prevention at the network layer gives regulated clients the assurance they need to put AI near sensitive data in the first place.
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