Overview Leaderboard Methodology
Industry Report

Anonymous Communication Apps

Messaging and calling applications designed to provide end-to-end encryption, metadata minimization, and features to protect user identity.

Brands tracked: 30
Brands analyzed: 30
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 245
Total responses: 96
Top Brand Overall?
Session
29/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Session
0

Highest score on the LBA metric in this industry.

Authority Leader?
Session
100

Highest score on the Authority metric in this industry.

TOM Leader?
S
Signal
77

Highest score on the TOM metric in this industry.

Anonymous Communication Apps is an emerging or highly fragmented category

No brand in Anonymous Communication Apps scored above 40 on overall AI visibility. That means AI assistants do not currently recommend specific brands for this category with any consistency. Either the category is too new or too regional for the models to have converged on a default set of answers, or the queries users ask don't lend themselves to brand-specific responses.

Brand Leaderboard All 30 Anonymous Communication Apps brands ranked

Ranked by overall AI Visibility Score (smoothed geometric mean of LBA, Authority, and TOM with an LBA-based floor on Authority and TOM, see methodology). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
Session
getsession.org
 0
100
73
29
2
S
Signal
signal.co
 0
69
77
26
3
SimpleX Chat
simplex.chat
 0
88
62
26
4
Briar
briarproject.org
 0
48
49
19
5
Threema
threema.ch
 0
25
46
15
6
Element
element.io
 0
13
13
7
7
CoverMe
coverme.ws
 0
0
11
2
8
Olvid
olvid.io
 0
6
0
1
9
Wire
wire.com
 0
0
5
1
10
Berty
berty.tech
 0
0
0
0
11
C
Confide
confide.com
 0
0
0
0
12
C
Conversations
conversations.im
 0
0
0
0
13
Cwtch
cwtch.im
 0
0
0
0
14
Delta Chat
delta.chat
 0
0
0
0
15
D
Dust
dust.app
 0
0
0
0
16
Ginlo
ginlo.net
 0
0
0
0
17
Jami
jami.net
 0
0
1
0
18
Keybase
keybase.io
 0
0
0
0
19
P
Pinngle
pinngle.me
 0
0
0
0
20
Ricochet Refresh
ricochetrefresh.net
 0
0
0
0
21
Silent Phone
silentcircle.com
 0
0
0
0
22
Skred
skred.mobi
 0
0
0
0
23
S
Speek
speek.network
 0
0
0
0
24
Status
status.app
 0
0
0
0
25
Tella
gettella.com
 0
0
0
0
26
Tox
tox.chat
 0
0
0
0
27
Twinme
twin.me
 0
0
0
0
28
Utopia
u.is
 0
0
0
0
29
Wickr
wickr.com
 0
0
1
0
30
Zangi
zangi.com
 0
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 245 shared Anonymous Communication Apps 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
Smoothed geometric mean of LBA, Authority and TOM. Authority and TOM are floored at LBA × 0.1 before the geometric mean (the same floor used in the per-metric cards above, so brand cards and the composite tell the same story). Formula: composite = ((LBA + 5)(Authority + 5)(TOM + 5))^(1/3) - 5. The floor keeps brands the model clearly recognises but doesn't yet recommend from collapsing to zero, while a single genuinely weak metric still pulls the composite down. Full methodology.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 245 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 →