European Energy Trader Accelerates Trading with Tufin AI-Assisted Policy Governance

Download the case study to see how a leading European energy trading business governs connectivity across seven enforcement technologies — including a 20,000-seat Zscaler deployment — with AI-assisted policy intelligence that provisions at trading-floor speed without trading away control.

The Challenge: Provisioning at Trading Speed Across an Estate Too Complex for Any One Engineer

• Seven Enforcement Technologies, One Trading Floor: Fortinet, Palo Alto, Cisco, and VMware on-premises, AWS and Azure in the cloud, and a large Zscaler SASE deployment — no engineer could reliably reason about what a proposed change would actually expose.
• From Execution to Judgement: With a mature automation practice already in place, the next constraint was not speed but quality of decision — knowing which policy action was correct across a hybrid estate too complex to hold in any one person’s head.
• Scale Without New Silos: Onboarding 1,500 additional cloud VMs and 20,000 Zscaler seats couldn’t come with new tooling, operational silos, or a new operating model for the team to absorb.

The Results: One Governance Model Across Firewalls, Cloud, and SASE — With Governed Autonomy

• 20,000 Zscaler Seats Under Intelligent Policy Governance: Scale absorbed in a single expansion with no new tooling or silos, and connectivity provisioned at the pace the trading floor requires — security is no longer the constraint on commercial speed.
• Better Decisions, Not Just Faster Ones: Policy intelligence surfaces the likely impact of every change across the whole estate, so engineers act on current analysis rather than institutional memory.
• Governed Autonomy at Scale: Routine, low-risk changes execute automatically within defined guardrails, while consequential decisions surface for human judgement with the analysis already attached.