Overview Leaderboard Methodology
Industry Report

Endpoint Detection and Response

Advanced platforms focused on continuous monitoring, threat detection, investigation, and automated response for endpoint incidents.

Brands tracked: 33
Brands analyzed: 33
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 263
Total responses: 1,330
Top Brand Overall?
CrowdStrike
96/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Microsoft
89

Highest score on the LBA metric.

Authority Leader?
CrowdStrike
100

Highest score on the Authority metric.

TOM Leader?
CrowdStrike
100

Highest score on the TOM metric.

CrowdStrike is the default answer in AI responses for Endpoint Detection and Response

CrowdStrike and Microsoft together dominate AI responses for Endpoint Detection and Response. Both brands consistently surface unprompted, with the model treating them as the default answers for most category queries. Brands outside the top two face a structural disadvantage: users are usually given these two before the model even considers alternatives.

Brand Leaderboard All 33 Endpoint Detection and Response brands ranked

Ranked by overall AI Visibility Score (geometric mean of LBA, Authority, and TOM). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
CrowdStrike
crowdstrike.com
 88
100
100
96
2
Microsoft
microsoft.com
 89
100
100
96
3
SentinelOne
sentinelone.com
 88
63
89
79
4
Sophos
sophos.com
 85
34
83
62
5
Trend Micro
trendmicro.com
 80
11
58
38
6
Palo Alto Networks
paloaltonetworks.com
 89
7
70
36
7
Huntress
huntress.com
 78
1
1
4
8
C
Carbon Black
carbonblack.com
 75
0
35
3
9
Cisco
cisco.com
 83
0
19
3
10
Trellix
trellix.com
 63
0
7
2
11
Cybereason
cybereason.com
 69
0
1
1
12
Cylance
cylance.com
 67
0
1
1
13
Fortinet
fortinet.com
 78
0
1
1
14
Acronis
acronis.com
 71
0
0
0
15
AhnLab
ahnlab.com
 57
0
0
0
16
Bitdefender Anti-Tracker
bitdefender.com
 41
0
0
0
17
Cynet
cynet.com
 61
0
0
0
18
Deep Instinct
deepinstinct.com
 57
0
0
0
19
ESET Secure Authentication
eset.com
 45
0
0
0
20
HarfangLab
harfanglab.io
 56
0
0
0
21
Heimdal
heimdalsecurity.com
 53
0
0
0
22
K7 Security
k7computing.com
 31
0
0
0
23
Kaspersky
kaspersky.com
 77
0
0
0
24
Malwarebytes Browser Guard
malwarebytes.com
 62
0
0
0
25
Morphisec
morphisec.com
 58
0
0
0
26
Panda Security
pandasecurity.com
 55
0
0
0
27
Seqrite
seqrite.com
 59
0
0
0
28
Tanium
tanium.com
 75
0
0
0
29
TEHTRIS
tehtris.com
 47
0
0
0
30
VIPRE
vipre.com
 53
0
0
0
31
WatchGuard AuthPoint
watchguard.com
 41
0
0
0
32
WithSecure
withsecure.com
 61
0
0
0
33
Xcitium
xcitium.com
 55
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 263 shared Endpoint Detection and Response prompts. The same prompts, same model, same iterations. So differences in scores reflect actual differences in AI visibility, not differences in measurement.

Overall AI Visibility Score
Geometric mean of LBA, Authority and TOM: (LBA × Authority × TOM)^(1/3). Geometric mean is used so that any single weak metric pulls the overall score down, rather than being masked by strength elsewhere.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 263 category prompts (e.g. "best SEO tools for agencies"). This makes brand-to-brand comparisons valid - everyone faces identical inputs. LBA prompts are per-brand because they ask brand-specific questions.
Latent Brand Association (LBA)
5 brand probes + 1 control prompt, each run 5 times in recall mode (no web search). LBA = quality × meta × stability × share × recognition × 100. Read the full LBA methodology →
LLM Authority
50 organic category prompts (discovery, comparison, problem and transactional intents), each run once in recall mode and once in retrieval mode. Score = frequency × log-decayed prominence × intent weight, then 50/50 averaged across the two modes. Read the full Authority methodology →
Top of Mind (TOM)
15 high-volume discovery prompts (sourced from Keywords Everywhere search-volume data), each run 5 times in pure recall mode (no web). Score = frequency × (0.5 + 0.5 × log-prominence), volume-weighted. Read the full TOM methodology →