Overview Leaderboard Methodology
Industry Report

Note-Taking and Personal Knowledge Apps

Applications focused on personal and team note capture, organization, and retrieval, often supporting rich text, attachments, and linking between notes.

Brands tracked: 34
Brands analyzed: 34
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 269
Total responses: 1,365
Top Brand Overall?
Obsidian
83/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Apple Notes
96

Highest score on the LBA metric.

Authority Leader?
Obsidian
75

Highest score on the Authority metric.

TOM Leader?
Notion
97

Highest score on the TOM metric.

Obsidian leads the Note-Taking and Personal Knowledge Apps category in AI responses

Obsidian is the most consistently-surfaced brand when users ask AI assistants about Note-Taking and Personal Knowledge Apps, but not to the point of monopolising the conversation. Notion and a handful of others appear regularly, giving users a reasonable set of alternatives to compare. The top of this leaderboard is where most of the AI-driven traffic will go.

Brand Leaderboard All 34 Note-Taking and Personal Knowledge Apps 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
Obsidian
obsidian.md
 88
75
85
83
2
Notion
notion.so
 84
68
97
82
3
OneNote
onenote.com
 85
68
88
80
4
Apple Notes
icloud.com
 96
40
72
65
5
Evernote
evernote.com
 83
36
82
63
6
Google
google.com
 80
24
62
49
7
Joplin
joplinapp.org
 71
12
25
28
8
Bear
bear.app
 71
3
48
23
9
Standard Notes
standardnotes.com
 67
13
7
19
10
Goodnotes
goodnotes.com
 86
3
21
18
11
Logseq
logseq.com
 72
5
8
15
12
Simplenote
simplenote.com
 68
0
31
10
13
Notability
gingerlabs.com
 84
0
7
6
14
Coda
coda.io
 84
0
6
2
15
Craft
craft.do
 66
0
21
2
16
UpNote
getupnote.com
 57
0
16
2
17
Agenda
agenda.com
 49
0
3
1
18
Amplenote
amplenote.com
 52
0
0
1
19
Anytype
anytype.io
 59
0
0
1
20
Nebo
myscript.com
 64
0
1
1
21
Nuclino
nuclino.com
 68
0
0
1
22
Reflect
reflect.app
 61
0
0
1
23
Roam Research
roamresearch.com
 78
0
2
1
24
Zoho Notebook
zohonotebook.com
 75
0
3
1
25
Capacities
capacities.io
 55
0
0
0
26
Dynalist
dynalist.io
 70
0
0
0
27
Heptabase
heptabase.com
 57
0
0
0
28
Inkdrop
inkdrop.app
 65
0
0
0
29
Mem
mem.ai
 61
0
0
0
30
Milanote
milanote.com
 73
0
0
0
31
Notejoy
notejoy.com
 49
0
0
0
32
RemNote
remnote.com
 66
0
0
0
33
Tana
tana.inc
 56
0
0
0
34
Workflowy
workflowy.com
 66
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 269 shared Note-Taking and Personal Knowledge 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
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 269 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 →