Security operations · AI-native

Security operations.Classically strong, AI-native in execution.

dynexo has been building and operating large security and network environments for two decades — from mid-market to critical platforms of national reach. Built on the leading components in the field: Cisco, Check Point, Palo Alto Networks, Fortinet. AI- and ML-driven detection and automation have been part of our day-to-day operations for years — not on a roadmap.

Large mandates · regulated sectors Models: EU · DE · on-premise Mid-market to large enterprise
Audited example · in your instance
Patch Tuesday · Cycle 2026-Q1
Workflow ID: WF-PATCH-042 · Audited in your instance
  1. 14:00
    AI
    Inventory pulled
  2. 14:02
    AI
    Risk classified
  3. 14:05
    Human
    Staging approved
  4. 14:10
    AI
    Test ring rolled out
  5. 14:25
    AI
    Test ring validated
+ 6 more steps Audited in your instance
What we operate today

The stack we know — layer by layer.

We don't recommend a component we haven't solved tickets with. We know the strengths, quirks and failure modes of the leading vendors — because we run them in production.

Firewalls & NGFW

  • Cisco
  • Check Point
  • Palo Alto Networks
  • Fortinet
  • Cisco Secure Firewall (SourceFire)

Configuration, hardening, audit. Operated in large mandates for more than two decades.

SASE / SSE

  • Palo Alto Prisma
  • Netskope
  • CATO Networks
  • Zscaler
  • Cisco Umbrella
  • Fortinet

Edge security, zero-trust access, inspection for hybrid workforces.

SD-WAN

  • Palo Alto Prisma SD-WAN
  • CATO Networks
  • Fortinet
  • Versa Networks
  • Cisco Viptela

Site interconnect, app-aware routing, integrated with security policy.

Datacenter SDN

  • Cisco ACI
  • VMware NSX
  • Arista CloudVision
  • HPE Aruba CX

Cisco ACI as the single source of truth for datacenter segmentation — large mandates, 100% automated.

Web & e-mail proxies

  • Zscaler
  • Cloudflare
  • Cisco WSA

Content filtering, SSL inspection, DLP pre-hooks, e-mail security (DMARC enforce).

Load balancers & ADC

  • F5
  • HAProxy
  • Citrix NetScaler
  • Cloudflare

High-availability publishing, TLS offload, WAF integration, application delivery.

Identity management

  • Microsoft Entra
  • Okta
  • Auth0

Lifecycle, federation, conditional access, sign-in risk, service accounts.

Privileged access management

  • CyberArk
  • Teleport
  • BeyondTrust

Just-in-time, session audit, four-eyes for admin access.

SIEM & detection

  • Splunk
  • IBM QRadar
  • FortiSIEM

Splunk operations in large estates. Correlation, detection engineering, runbooks.

OT gateways & segmentation

  • Fortinet
  • Cisco IE
  • Claroty
  • Nozomi Networks
  • Dragos

Safe bridges between IT and OT. Detection rather than blind blocking.

Assessments & pentests

  • Burp Suite Pro
  • Metasploit
  • Nmap
  • PentestGPT

Architecture reviews, pentests and red-team exercises — Burp, Metasploit and Nmap, paired with LLM-driven recon and reporting where customers allow.

Vendor-neutral in advice, hardened in practice. Network & security: Cisco · Check Point · Palo Alto · Fortinet · Versa · CATO · VMware NSX · Arista · HPE Aruba. Edge & SSE: Netskope · Zscaler · Cloudflare · Cisco Umbrella. Identity & PAM: Microsoft Entra · Okta · Auth0 · CyberArk · Teleport · BeyondTrust. SIEM: Splunk · IBM QRadar · FortiSIEM. OT: Claroty · Nozomi · Dragos · Cisco IE.

Standardisation

Business rules in code. Everything else around them.

We learned it on large Cisco ACI mandates: 100% automation and AI only hold up when a single, versioned source of truth lies beneath them. We encode security and business rules as code — one source. Processes, automation and agents move inside those rules.

  • One source

    Security and business rules live in code, versioned. No Excel exports, no shadow configurations, no drift. Diffable, auditable, traceable.

  • Cites the rule

    Every workflow references the policy it checks against. We always know why a decision went one way and not the other.

  • Stays inside

    AI can act, but never past policy. Vendor changes cost time, not control. The rules outlive the tooling.

  • Traces to the rule

    Every agent action traces back to the rule that authorised it. No black-box behaviour, no scrambling for an explanation in front of an auditor.

Example · LLM Gateway policy in Starlark
def on_request(req):
    if req.contains_pii() and not req.user.has_role("dpo"):
        return deny("PII without DPO approval")
    if req.tokens > budget.daily_remaining(req.tenant):
        return route("fallback-model")
    return allow()
Field record

Where it held.

Security vendors are not allowed to name clients. What we can name are the patterns — and the outcomes. Two examples from our practice.

DACH industrial group · multi-site environment · migration to a modern security standard for industrial environments

Active ransomware against the group. Where the overlay had landed, nothing broke.

We designed the security overlay and implemented a modern security standard for industrial environments. The standard has held under active attack across multiple mandates — industrial and critical power-supply infrastructures. The most prominent: a DACH industrial group hit several times during the migration. Everything already migrated stayed available.

Availability of migrated sites
100%
Encrypted systems in scope
0
Ransom discussion
none
Industrial Ransomware Segmentation Overlay OT/IT
Utility · critical platform with national reach

Platform built, secured, operated — and handed over clean.

Security architecture and network platform built on the leading security and network components, enhanced by our own AI/ML layer for detection and automation. Two years of operations by dynexo. Clean hand-over in 2022 — the customer has run it independently since.

Platform live
since 2020
Operational ownership
2 years
Hand-over without incident
2022
Customer operating
self-sufficient
Utility Critical infrastructure AI/ML Hand-over

More detailed reports from our mandates are on the »About« page.

What changed

What Claude Code was for software teams, Nova9 is for IT operations.

An industry shift that already happened in software engineering — and is just as inevitable for IT operations.

In engineering

Vibe-coding with Claude Code & co.

80–90%
of code is now generated by AI
Before
Teams of 30+ engineers ship a product.
Today
2–3 senior engineers design and steer. AI writes the code.
Scaling
More model time, more context — not more headcount.
In IT operations

Nova9 AgentOS for operations.

80–90%
of routine handled by our agent fleet
Before
Large admin teams or external system integrators process tickets by hand.
Today
A few experts design processes. Agents execute. You stay in control.
Scaling
More agents, more models — not more staff.

The model isn't "small vendor vs large vendor." The model is different.

The platform

Nova9 AgentOS — the operating system for your agent fleet.

Async, distributed, fully audited. Not a script with an LLM API behind it, but a real platform with message bus, observability and safety layer.

Async message bus
Distributed agents communicate over a resilient message bus. No SSE toy. Agents keep working even when a model is slow or down.
Full observability
Every tool call, every LLM request, every decision — searchable inside your own system. You see what the agents do for you.
Safety & security
Guardrails at multiple layers. Sandboxed tool execution. Rollback-capable actions. Two-person approval for production-critical steps.
Multi-tenant
One platform instance, many customers — or a dedicated instance just for you. You decide where the boundary runs.
Fully cloneable
The whole Nova9 platform fits in a VM. We deliver your clone — processes, tools, knowledge base. Handover with no lock-in.
Your models
Models run in the EU, Germany or on your own infrastructure. Data and logs never leave your perimeter.
What Nova9 ships with

Six modules. One platform.

Each module is usable on its own — or as a full system run by our team.

01 Gateway

LLM Gateway

Our own layer in front of every model. Guardrails, input/output normalisers, model tuning, budgets, rate-limits, full audit log.

Guardrails Budgets Audit Routing
02 Business

Business Agents

Agents that connect to your business systems — ERP, CRM, ticketing, mail, file systems. Not private chat toys; integrated into real operations.

ERP CRM M365 Ticketing
03 Endpoint

Endpoint Agents

Autonomous agents on your clients. You can go home — the client keeps working: answering requests, running routines, solving problems.

Windows macOS Linux autonomous
04 Knowledge

Knowledge Base

Years of curated sys-ops knowledge. Endpoint Agents get answers that would otherwise be scattered across forums — contextual and direct.

Sys-Ops Runbooks Context curated
05 Bus

Async Message Bus

Distributed and resilient. Agents work in parallel and communicate reliably. No SSE bottleneck, no lost actions.

Async distributed durable
06 Observe

Observability

Every action, every LLM call, every tool use — structured, searchable, exportable. Your audit trail stays with you.

Tracing Audit Replay
Sovereignty, built in

The big AI vendors want your data. We build the opposite.

Sovereignty here isn't marketing — it's architecture. Every layer is designed so you stay in control, including over us.

  • Models
    EU, Germany or on-premise
    We run whatever model is permitted in your environment — EU-cloud through air-gapped on-prem. Your choice, not ours.
  • Data
    never leaves your perimeter
    Training and inference data stay in your infrastructure. We don't see business data unless you explicitly approve it.
  • Logs
    stay with you
    Audit logs, tool calls, model outputs — all in your system, searchable by you. We don't keep shadow copies.
  • Platform
    cloneable at any time
    Your Nova9 instance fits in a VM. We deliver the snapshot — you can run the platform yourself whenever you want.
  • Gateway
    safe access to public LLMs
    When you need a public model — GPT, Claude, Gemini — we route it through our gateway with filters, redaction and budgets.
  • Lock-in
    doesn't exist
    No proprietary format, no hidden binding. What we build is yours — as code, with documentation.
A day in Nova9

Example: a patch rollout, fully driven by the agent fleet.

A real, anonymised sequence. Three human decisions, the rest by the agent fleet. Every action in the audit log inside your system.

Patch Tuesday · Cycle 2026-Q1
Workflow ID: WF-PATCH-042 · Audited in your instance
1:58 hDuration
3Human decisions
69 / 70Hosts patched
1Rollbacks
  1. 14:00
    AI
    Inventory pulled
    Vendor feeds (Microsoft, RedHat, Cisco) consolidated. 47 new CVEs identified.
  2. 14:02
    AI
    Risk classified
    12 CVEs marked critical. 81 affected assets mapped.
  3. 14:05
    Human
    Staging approved
    Ops lead confirms staging plan for the test ring (12 hosts).
  4. 14:10
    AI
    Test ring rolled out
    Ansible playbook applied to 12 hosts. Service health checked.
  5. 14:25
    AI
    Test ring validated
    Logs, latency and error rates within thresholds. No regress.
  6. 14:30
    Human
    Production approved
    Analyst reviews validation report, releases waved rollout.
  7. 14:32
    AI
    Wave 1/3 · 24 hosts
    Rolling update, max 8 parallel. Health-check after each batch.
  8. 15:04
    AI
    Wave 2/3 · 24 hosts Auto-rollback
    Continues. One host showed elevated CPU — auto-rolled back.
  9. 15:18
    Human
    Triage wave-2 anomaly
    Investigation of CPU spike on srv-app-17. Patch rescheduled.
  10. 15:46
    AI
    Wave 3/3 · 21 hosts
    Remaining hosts patched successfully.
  11. 15:58
    AI
    Report generated
    PDF + audit log generated, attached to ticket, mailed to CISO.
Anonymised excerpt of a real run — Q1 2026, mid-market mandate. Logged inside the customer instance.
Our mission

We replace dull work. So humans can do interesting things.

Routine IT operations is exhausting: triage tickets, push patches, create accounts, scroll logs, answer the same question a thousand times. The work matters — but nobody trained for it, it's nobody's calling.

We build agents that take it over. Not perfect on day one, but better every day. Every action grows the knowledge base. Every piece of feedback tunes the model.

What remains is the interesting work: designing architecture, investigating hard incidents, talking to people. The reason most IT experts started in the first place.

How it starts

Three phases to a productive handover.

01
Conversation
30 minutes. We map your stack, your bottlenecks and your sovereignty requirements.
02
Pilot
4–6 weeks. One Nova9 module runs in production on your data. You see real workflows, not demos.
03
Handover
Rollout across more modules. Optional: a fully cloned instance you operate yourself.
Next step

See Nova9 in action.

45-minute live demo of the platform against your use-cases. No sales deck — we show the actual modules, the actual audit log, the actual message bus. You decide whether a pilot makes sense.