Case study — Zero-trust mesh

6,000+ endpoints. Not one breach made it past the front door.

A private zero-trust mesh spanning three production datacenters. Every endpoint isolated into its own segment. AI agents monitoring every flow, twenty-four hours a day — while the client's team sleeps.

6,000+ endpoints
under management
~1,000 isolated network
segments
3 + DR production datacenters
active-active + DR site
0 successful
lateral movements

The problem

Most enterprise networks still work on the castle-and-moat model. Once you're in, you're in.

"Traditional VPNs give blanket access — one compromised credential and an attacker can move anywhere on the network. Most breaches aren't stopped at the perimeter; they're discovered weeks later during a forensic audit, long after the damage is done. The question isn't whether to get breached — it's whether your network can contain and respond before you even know it happened."

Dimension Traditional VPN / flat network X402 zero-trust mesh
Breach containment One credential compromise = full network access ~1,000 isolated segments — breach is contained to one
Lateral movement Unchecked once the perimeter is crossed Structurally impossible between segments by design
Access model Blanket access to all resources on the VPN Every endpoint authenticates to every resource, every time
Threat response Human security team needed 24/7 — gaps at night and weekends AI agents isolate compromised endpoints in seconds, around the clock
Encryption at rest Optional, inconsistent, often skipped LUKS full-disk on every server — non-negotiable
Failover Manual DR switchover, often untested until needed Active-active: if one datacenter goes dark, every tunnel continues automatically

The network topology — live

Each dot is an endpoint. Each cluster is an isolated segment. When AI detects a threat, watch what happens.

AI security monitoring — every flow · every endpoint
6,000+ endpoints
~1,000 segments
3 + DR datacenters
0 events today
Security event log

Technical depth

What makes it work — and stay working

~1,000 isolated segments — blast radius by design

Each customer's network is carved into a catalog of isolated segments. An attacker who compromises one endpoint is structurally contained — they can see exactly nothing outside their segment. Blast radius is drawn before deployment, not discovered during the post-mortem. Multi-tenant: multiple organizations share the same infrastructure with hard cryptographic boundaries between them.

network segmentation zero-trust multi-tenant

LUKS encryption at rest — every disk, non-negotiable

Every server in the mesh runs full-disk encryption — LUKS on Linux, native encryption on Windows. If a physical machine is ever removed from a datacenter, the data on it is unreadable. Encryption at rest is not a checkbox here — it's structural and verified. Combined with encrypted tunnels in transit, data is protected end-to-end and on-device.

LUKS full-disk encryption in-transit + at-rest

Active-active replication — if one datacenter goes dark, nothing stops

The mesh spans two primary datacenters in active-active configuration: both handle full production load simultaneously. If one goes offline — power, network, hardware failure — the other datacenter carries every active tunnel with no manual intervention. A dedicated DR site on a separate continent is ready to activate if both primary sites are affected. Continuity is automatic, not a recovery procedure.

active-active multi-continent DR auto-failover

AI egress agent — threats isolated in seconds, not hours

AI agents inspect every flow across the mesh in real time — detecting credential sprays, flagging lateral movement attempts, catching data exfiltration patterns. When the egress agent confirms a compromise, it quarantines the endpoint and alerts the responsible team immediately, before the breach can propagate. BYOIP egress means outbound traffic carries the client's own IP space — fully attributable, no shared reputation.

AI security agents egress monitoring BYOIP

What it delivers

A network that defends itself — by design, not by hope.

6,000+ endpoints under continuous AI monitoring
~1,000 isolated segments — every breach contained before it spreads
Seconds from threat detection to endpoint isolation — not hours, not days
24/7 AI agents on watch — the network defends itself while your team sleeps

Ready to talk security?

Is your network still counting on the perimeter to hold?

Most organizations discover their flat network model during a breach audit — too late. We design for the assumption that endpoints will be compromised, and build accordingly. Tell us what your network looks like today; we'll tell you where the gaps are.

Talk to us about network security See all case studies
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