Trellix AI Visibility Market Strategy Report - Endpoint Detection and Response Software

Answer Capsule

Trellix holds almost no recommendation-stage visibility in the Endpoint Detection and Response Software category, despite being tracked across all six AI platforms in the October 2026 benchmark. The LLM Authority Index recorded a 7.89% raw mention presence rate for Trellix, but only a 2.56% valid recommendation coverage rate, meaning the brand is referenced far more often than it is actually recommended. Its sentiment score of 0.325 is the lowest among all ten tracked brands, and its clearest weakness is a rank-one rate of 0.00%, with zero first-position recommendations across 507 qualified observations. The clearest opportunity is converting existing neutral mentions into valid recommendations within the Best EDR Platform Discovery and Evaluation cluster, where all 507 qualified observations currently sit.

Who This Report Is For

This report is for Trellix marketing, product marketing, and demand generation leaders who need to understand why the brand appears in AI-generated answers but is almost never selected in the buyer shortlist, and what that pattern means for competitive positioning in AI-led discovery.

Report Card

Executive Summary

Trellix is visible in the Endpoint Detection and Response Software category but is not being recommended. Across 507 qualified observations in October 2026, the LLM Authority Index recorded a raw mention presence rate of 7.89% for Trellix, yet valid recommendation coverage of only 2.56%. That gap between being mentioned and being recommended is the central finding of this report.

The brand's mention profile is thin and skewed toward neutral framing. Of the 40 observations where Trellix appeared, 27 were neutral, 13 were positive, and none were negative. The resulting net sentiment score of 0.325 is the lowest of any tracked brand in the category, well below CrowdStrike Falcon at 0.8103, Microsoft Defender for Endpoint at 0.8024, and SentinelOne at 0.817. Trellix is being referenced, but the framing around those references is weaker than the category norm.

Recommendation placement is the sharper problem. Trellix recorded a top-three rate of 0.39% and a rank-one rate of 0.00%, meaning the brand appeared among the top three recommended options in just 2 of 507 qualified observations and never appeared as the first recommendation. Its average recommended rank of 6.3846 places it well behind the category leaders and behind most mid-tier competitors.

The strongest cluster for Trellix is the only cluster with qualified data: Best EDR Platform Discovery and Evaluation, which carries a consideration-stage buyer intent. All 507 qualified observations in October 2026 fell into this cluster. The EDR Platform Pricing and Cost Evaluation and EDR Platform Comparison and Competitive Evaluation clusters returned no qualified observations in the public benchmark, so Trellix's performance in those commercial-intent contexts cannot be assessed from this dataset.

Platform-level data shows Trellix's strongest signal on Google AI Mode, where it recorded a 4.00% valid recommendation coverage rate and a 0.4167 net sentiment score. Its weakest platform signal is on Copilot, where it recorded a 2.94% valid recommendation coverage rate but zero recommendation value, and on Gemini, where it recorded a single valid recommendation at rank 10. The brand has no measurable recommendation presence on ChatGPT beyond a 4.23% coverage rate with no rank-one placements.

The clearest gap is competitive displacement. Microsoft Defender for Endpoint, the cluster winner, holds a 50.69% top-three rate and a 7.30% rank-one rate. CrowdStrike Falcon holds a 61.34% top-three rate and a 43.59% rank-one rate. Trellix's 0.39% top-three rate and 0.00% rank-one rate place it at the bottom of the tracked set alongside VMware Carbon Black and Cybereason.

What Trellix Is Winning

Questions This Section Answers

• On which platform does Trellix show its strongest recommendation coverage and sentiment?
• Does Trellix have any negative mentions in the October 2026 benchmark?

Trellix has very few measurable wins in this benchmark, and the report should be read with that context. The brand does show one narrow but meaningful signal: on Google AI Mode, Trellix recorded a 4.00% valid recommendation coverage rate, which is its highest platform-level coverage figure. That platform also produced the brand's highest net sentiment score at 0.4167, suggesting that when AI Mode does surface Trellix, the framing is more favorable than on other platforms.

The brand also recorded zero negative mentions across all 507 qualified observations. While this is a weak positive given the low overall mention volume, it does indicate that Trellix is not being actively framed negatively in AI-generated answers. The absence of negative framing is a baseline condition the brand can build on, but it is not a competitive advantage on its own.

Beyond these two observations, the data does not support claims of category leadership, strong recommendation power, or competitive displacement in any cluster or platform.

Where Trellix Has the Clearest AI Visibility Gaps

Questions This Section Answers

• Why is Trellix mentioned so often but rarely recommended?
• How does Trellix's top-three and rank-one rate compare to category leaders like CrowdStrike Falcon and Microsoft Defender for Endpoint?
• Which competitor-owned domains dominate the AI citation layer where Trellix is absent?

The clearest gap is the distance between mention presence and recommendation conversion. Trellix appeared in 40 of 507 qualified observations, but was recommended in only 13. That means roughly two-thirds of the time Trellix is mentioned, it is not included in the valid recommendation shortlist. By contrast, CrowdStrike Falcon appeared in 448 observations and was recommended in 340, a conversion pattern that reflects strong recommendation-stage visibility.

Competitive displacement is severe. Microsoft Defender for Endpoint, the cluster winner for Best EDR Platform Discovery and Evaluation, holds a 50.69% top-three rate and a 7.30% rank-one rate. CrowdStrike Falcon holds a 61.34% top-three rate and a 43.59% rank-one rate. SentinelOne holds a 45.96% top-three rate and a 4.54% rank-one rate. Trellix's 0.39% top-three rate and 0.00% rank-one rate place it in a different tier entirely.

The brand is also absent from the top of the recommendation set on every platform. On ChatGPT, Trellix recorded a 4.23% valid recommendation coverage rate but zero rank-one placements. On Copilot, it recorded a 2.94% coverage rate with zero recommendation value. On Gemini, it recorded a single valid recommendation at rank 10. On Perplexity, it recorded a 1.85% coverage rate with a single valid recommendation at rank 9. On AI Overviews, it recorded a 0.84% coverage rate with a single valid recommendation at rank 8. Only on Google AI Mode did Trellix record a coverage rate above 4%, and even there it recorded zero rank-one placements.

The source layer offers one additional signal. Among the top 10 cited domains across all AI platform responses in this measurement period, no Trellix-owned domain appears. SentinelOne's domain ranks third with 203 citations, CrowdStrike's domain ranks sixth with 135 citations, and Palo Alto Networks' domain ranks seventh with 129 citations. Microsoft's domain and learn.microsoft.com rank eighth and ninth. Trellix's absence from the top cited domains suggests the brand's public evidence layer is not being retrieved or synthesized at the same rate as its competitors.

Biggest Opportunity

Questions This Section Answers

• What is the highest-leverage way for Trellix to convert neutral mentions into valid recommendations?
• Which buyer cluster should Trellix prioritize to improve recommendation-stage visibility?

The single biggest opportunity for Trellix is converting existing neutral mentions into valid recommendations within the Best EDR Platform Discovery and Evaluation cluster. The brand already appears in 40 of 507 qualified observations, which means AI systems are retrieving Trellix content or references. The problem is that those appearances are not converting into shortlist inclusion. Of the 40 mentions, 27 were neutral, meaning the AI system referenced Trellix without framing it as a recommended option.

Closing that gap requires targeted work on the prompt, page, and citation layers that shape how AI systems frame Trellix when the brand is retrieved. The highest-leverage starting point is the Best EDR Platform Discovery and Evaluation cluster, where all 507 qualified observations currently sit. Within that cluster, the prompts that produce neutral mentions rather than recommendations are the ones worth mapping first.

Competitive Landscape

Questions This Section Answers

• Where does Trellix rank among the ten tracked EDR brands on top-three and rank-one recommendation rates?
• How does Trellix's sentiment compare to CrowdStrike Falcon, Microsoft Defender for Endpoint, and SentinelOne?

CrowdStrike Falcon and Microsoft Defender for Endpoint hold the strongest recommendation-stage positions in the Endpoint Detection and Response Software category, with SentinelOne close behind. Trellix sits at the bottom of the tracked set on both top-three and rank-one rates, alongside VMware Carbon Black and Cybereason.

Average recommended rank covers rank-eligible recommendations only.

Trellix's position in the table reflects a brand that is mentioned but not selected. Its 0.39% top-three rate and 0.00% rank-one rate place it below Trend Micro and just above Cybereason and VMware Carbon Black, both of which also recorded zero rank-one placements. The sentiment score of 0.325 is the lowest in the tracked set, indicating that even when Trellix is mentioned, the framing is weaker than the category norm.

Prompt Evidence

Questions This Section Answers

• What do the prompt-level examples show about when Trellix is mentioned versus when it is actually recommended?
• Which platforms produced Trellix's only measurable recommendation placements?

Google AI Mode / Best EDR Platform Discovery and Evaluation Prompt: "What are the most popular antivirus programs?" Result: Trellix appeared in the response but was not included in the valid recommendation shortlist, contributing to the brand's neutral mention count.

ChatGPT / Best EDR Platform Discovery and Evaluation Prompt: "Which is the best SIEM tool?" Result: Trellix was mentioned but not recommended, with the response favoring higher-coverage brands such as CrowdStrike Falcon and Microsoft Defender for Endpoint.

Perplexity / Best EDR Platform Discovery and Evaluation Prompt: "endpoint detection and response software" Result: Trellix received a single valid recommendation at rank 9, its only measurable recommendation placement on Perplexity.

Google AI Overviews / Best EDR Platform Discovery and Evaluation Prompt: "endpoint security tools" Result: Trellix received a single valid recommendation at rank 8, its only measurable recommendation placement on AI Overviews.

What CiteWorks Studio Would Do Next

Phase 1: AI Visibility Market Discovery Audit Map the specific prompts and platforms where Trellix is mentioned but not recommended, and identify which competitors are taking the recommendation slot instead.

Phase 2: Recommendation Readiness Plan Prioritize the neutral-mention prompts that are closest to converting into valid recommendations, and define the framing changes needed to move Trellix into the shortlist.

Phase 3: Owned Answer Layer Buildout Strengthen Trellix-owned pages and documentation so AI systems retrieve clearer, more recommendation-ready language when the brand is surfaced.

Phase 4: Citation / Authority Layer Development Build the public evidence layer that AI systems cite, including analyst references, comparison pages, and third-party validation that supports recommendation-stage framing.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track Trellix's top-three rate, rank-one rate, and sentiment score month over month to measure whether neutral mentions are converting into valid recommendations.

Why This Matters

AI presence alone is not enough. Trellix is mentioned in AI-generated answers, but it is almost never recommended. In a buyer shortlist context, a neutral mention is not the same as a recommendation, and the data shows that Trellix is losing the recommendation stage to competitors with stronger citation and framing signals.

The next move is targeted correction of the prompt, page, and citation layers that shape how AI systems frame Trellix. The brand does not need to start from zero. It needs to convert existing mentions into recommendations by improving the evidence and framing that AI systems retrieve when Trellix is surfaced.

Core Metrics

Sentiment Score

Sentiment Score = (positive mentions × 1 + neutral mentions × 0 + negative mentions × -1) / total mentions

For Trellix, that calculation is (13 × 1 + 27 × 0 + 0 × -1) / 40 = 0.325.

This matters because unclassified mention counts are misleading. A brand that appears in 40 AI responses but is only positively framed in 13 of them is not in the same position as a brand with 40 positive mentions. Share of voice is a diagnostic metric, not a business KPI. A positive recommendation, a neutral reference, a cautionary mention, and a competitor-displaced mention are not equal.

Counting all mentions as wins is bad measurement. Trellix's 40 mentions include 27 neutral references where the brand was named but not recommended. Those mentions do not represent buyer shortlist inclusion. Classified sentiment is required before interpreting AI visibility, and in Trellix's case, the classification shows that the brand's mention profile is skewed toward neutral framing rather than positive recommendation.

Sentiment by Platform

Methodology

1. This report is a benchmark-based analysis of Trellix's AI visibility in the Endpoint Detection and Response Software category, using data from the LLM Authority Index October 2026 measurement period.
2. The reporting month is October 2026, with baseline comparisons drawn from July 2026 where available.
3. Six AI platforms were tracked: ChatGPT, Copilot, Gemini, Perplexity, Google AI Overviews, and Google AI Mode.
4. The benchmark analyzed 507 qualified observations in October 2026, drawn from an initial collection of 800 prompt-surface observations.
5. The competitor universe includes ten tracked brands: Bitdefender GravityZone, CrowdStrike Falcon, Cybereason, Microsoft Defender for Endpoint, Palo Alto Cortex XDR, SentinelOne, Sophos Intercept X, Trellix, Trend Micro, and VMware Carbon Black.
6. Three public high-intent clusters were defined: Best EDR Platform Discovery and Evaluation, EDR Platform Comparison and Competitive Evaluation, and EDR Platform Pricing and Cost Evaluation. Only the first cluster returned qualified observations in October 2026.
7. Stage 0 extraction was used to qualify observations, separating relevant from irrelevant prompts and establishing the public denominator for brand-level metrics.
8. A mention is defined as any appearance of the brand in an AI-generated response, regardless of whether the brand was recommended.
9. A valid recommendation is defined as an appearance in a recommendation shortlist where the brand was explicitly recommended, not merely referenced or listed as context.
10. Brand-level percentages are calculated against the 507 qualified observations, not the raw 800 prompt-surface observations collected.
11. The public benchmark does not measure market share, revenue, pipeline conversion, or causality from metric movement alone.
12. Unique prompt count is not available in the public version of this benchmark. The qualified observation count serves as the public denominator for all brand-level metrics.

See How AI Is Recommending Your Brand

The public benchmark shows where Trellix is being mentioned and where it is being recommended. A company-level AI visibility audit maps the specific prompts, platforms, competitors, and citation sources that shape those outcomes into a prioritized strategy for improving recommendation-stage visibility.