Industry · Cybersecurity

Be the security vendor AI engines name when a CISO builds a shortlist.

EDR and XDR, MDR, SIEM, identity, GRC, managed security. ZivRank measures which vendors AI engines name on your buying questions, then works to get your brand into those answers.

Check my AI visibility → How we measure

Security buyers ask precise questions: frameworks, deployment models, integrations, compliance evidence. A generic answer does not survive a CISO. Neither does generic content.

What we bring to cybersecurity

Built for how your buyers research

Compliance-led questions

SOC 2, HIPAA, PCI DSS, CMMC, FedRAMP, the SEC cyber disclosure rules: buyers ask AI engines how vendors help them meet a requirement. We map those questions first.

Category by category

EDR, MDR, SIEM, identity, email security, vulnerability management and GRC each have their own buying questions and their own set of vendors that get named.

Expert review, every asset

Nothing technical goes live without an expert read. One wrong claim costs more trust with a security buyer than ten good articles earn.

Buying questions

What your buyers ask AI engines

Examples of the questions we measure for cybersecurity vendors. Your own list is built and validated with you before the first measurement.

“Best MDR provider for a mid-market company”

“Which EDR works best for a lean IT team”

“SIEM alternatives for a company with no SOC”

“Tools to prepare for a SOC 2 Type II audit”

“How to meet CMMC Level 2 as a defense subcontractor”

“Managed security provider for HIPAA-covered entities”

“Identity security platform comparison for Okta shops”

“Vulnerability management tools that prioritize by exploitability”

Sources

Where the answers come from

Security answers lean on analyst-style comparisons, vendor documentation, community threads and review platforms. We measure which of them the engines actually reuse for your questions before deciding where your content should live.

Proof, not promises

Measured before and after

Every program starts with a locked baseline measurement and is re-measured with the same protocol. You keep the raw answers, so every number in your report can be checked. See a measured case study →

The method, applied to cybersecurity

From baseline to re-measurement

Measure

The buying questions of your market (50 from the Core plan upward), asked 5 times on each of 5 AI engines. You see where you are named, where you are only a source, and where you are absent.

Diagnose

Who is named instead of you, on which questions, and which sources the engines reuse. Plus a technical audit of what stops AI engines from reading your site.

Produce

Assets the engines can cite, placed on the sources they already trust in cybersecurity. Reviewed by an expert before anything goes live.

Re-measure

The same protocol, replayed identically. A change only counts if it rises above the noise floor set before comparison.

FAQ · Cybersecurity

Frequently asked questions

How do I get my security product mentioned by ChatGPT?

Start by measuring: list the buying questions your prospects ask, run them several times on each engine, and see who is named. Then fix what blocks AI crawlers on your site and publish precise, verifiable content on the sources the engines already reuse for those questions.

Do CISOs really use AI engines to research vendors?

B2B buyer surveys show generative AI is now a common step in software research, and buyers also say they verify AI answers with vendors and peers. Being named in the answer gets you into the conversation; it does not replace it.

Can you cover MSSP and MDR providers, not only products?

Yes. Service providers have their own buying questions ("managed security provider for…", "MDR vs in-house SOC"). We measure them separately from product questions.

How do you handle competitor comparisons in security?

Comparisons must be accurate and sourced. We position your brand on the criteria where it genuinely wins, and we never publish a claim we cannot back.

How long before results show up?

Our observed pickup time is 3 to 8 weeks: that is how long AI engines take to pick up a published asset. We re-measure after that, and a change only counts if it rises above the noise floor set before comparison.