u/Acrobatic-Layer9109

We are a ZIA/ZPA shop, roughly 4,000 seats, renewal in about seven months. Not shopping for the sake of it, but the AI requirements landed after our last contract and I want to know whether we are better off expanding here or looking at Cato.

Where we are with Zscaler on the AI side: SSL inspection is solid, the AI app category exists, DLP works about as well as our policies deserve. What I am less clear on is inline prompt-level control versus app-level allow/block, and how much of the newer AI functionality is included versus a separate SKU.

The Cato pitch we got leaned heavily on single-pass processing and one policy engine covering network, security, and AI, plus their inline inspection story. Sounded clean in the demo. Skeptical of demos.

Asking here specifically because I want the incumbent perspective: if you have added AI controls on top of an existing ZIA deployment, was it configuration or a new purchase; how has inspection performance held up on streaming LLM responses; has anyone actually evaluated Cato head to head and stayed, and what kept you; and for anyone who left, what was the deciding factor?

Requirement is to prevent sensitive content such as source code, customer PII, and unreleased financials from being submitted to public LLM interfaces, while still allowing general use of those tools. Not a full block. Leadership wants the productivity.

for now What I have tested and where it fell short... domain blocking is blunt, users route around it, and it kills the productivity case..cuz endpoint DLP catches copy from managed apps but misses typed or paraphrased content entirely and CASB in API mode is after the fact, too late.

What I think I need is inline inspection of the POST body at the gateway with real DLP classifiers running against it, applied per-user or per-group.

Two things I want a sanity check on: whether anyone is getting acceptable false-positive rates doing content inspection on prompts, given that prompts are messy text and my worry is a classifier tuned for documents will scream constantly; and how to handle the mobile or unmanaged-device path where you cannot force traffic through the gateway.

Vendor recommendations welcome but I am more interested in whether this approach actually holds up operationally.

An auditor called us out last cycle for having controls mapped to the framework but no ongoing evidence that they were actually operating every day. Fair point, honestly, because our whole process was point-in-time. We would map every control back to the framework once a year, take screenshots, do interviews, and call it done.

The problem is that the moment the audit closes, the evidence is already stale. A control can break the next week and we would not know until the next cycle, if we caught it at all. Has anyone found a way to keep evidence current instead of rebuilding the same snapshot over and over?

Trying to untangle our container security story and hitting the point where vendor decks all sound good, but I don't fully trust any of it.

Context: mix of on-prem and cloud, multiple clusters, legacy moving into containers, and some FedRAMP-ish environments. No greenfield. No rip-and-replace.
We've got the basics: image scanning in the pipeline, runtime protection, deployment policies. But in practice it feels fragile.

The gaps:

• Different tools for scanning, runtime, and policy, no single view
• Tons of critical-looking findings that are actually low-risk in context
• Devs using sidecars or third-party containers we don't fully control
• Compliance needs audit trails and evidence, but tools give dashboards instead

I'm looking for what's come closest to working end-to-end in an enterprise or public sector setting, from people who've lived with it long enough to know if it actually made daily life easier.

For anyone running this in a mixed on-prem/cloud setup: any surprises with admission controls, policy-as-code, or service mesh interactions once it was live?

asking because I think our process is broken. every year it's the same cycle: emails to app owners, spreadsheets, chasing down evidence that's stale by the time it's compiled. last cycle took close to two months.

is anyone doing this in near real time now or is everyone still stuck in the same manual evidence loop?

we're eu-facing enough that this isn't optional. And every consultant conversation so far has been heavy on documentation and risk classification paperwork...like light on what technical controls need to exist underneath it.

now what i can't get a straight answer on is whether ai compliance and eu ai act readiness can be documentation alone or whether an assessor is going to want to see the technical control running, not just described.

and specifically around the testing and monitoring obligations for high-risk systems, is a written risk assessment enough or do they expect live evidence of testing happening?

podting here to understand...for anyone further along on eu ai act prep than us, where did the documentation-only approach fall short once you got closer to an actual assessment?