Overview Leaderboard Methodology
Industry Report

Expense Management Platforms

Platforms that help companies capture, approve, and reconcile employee expenses and receipts, often integrating card feeds and accounting systems.

Brands tracked: 37
Brands analyzed: 37
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 287
Total responses: 1,470
Top Brand Overall?
Ramp
94/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Ramp
87

Highest score on the LBA metric in this industry.

Authority Leader?
Ramp
96

Highest score on the Authority metric in this industry.

TOM Leader?
Ramp
100

Highest score on the TOM metric in this industry.

Ramp is the default answer in AI responses for Expense Management Platforms

When users ask ChatGPT, Claude, or Gemini about Expense Management Platforms, Ramp is the brand that surfaces first - unprompted, consistently, and usually at the top of any list the model generates. Expensify is a close second, but the gap between them is meaningful. If you're competing in this space and you're not in the top handful, you're effectively invisible to AI-driven discovery.

Brand Leaderboard All 37 Expense Management Platforms 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
Ramp
ramp.com
 87
96
100
94
2
Expensify
expensify.com
 70
82
93
81
3
Brex
brex.com
 87
58
89
77
4
SAP Concur
concur.com
 75
56
90
72
5
Zoho
zoho.com
 80
46
72
64
6
Navan
navan.com
 70
8
27
27
7
Airbase
airbase.com
 66
7
27
25
8
QuickBooks Live
intuit.com
 69
13
13
24
9
BILL
bill.com
 79
8
15
23
10
Coupa
coupa.com
 78
8
16
23
11
Emburse
emburse.com
 67
7
20
23
12
Pleo
pleo.io
 72
7
17
22
13
Rippling
rippling.com
 70
7
17
22
14
Spendesk
spendesk.com
 61
6
15
20
15
Rydoo
rydoo.com
 59
6
14
19
16
Xero
xero.com
 72
7
7
18
17
Divvy
getdivvy.com
 71
7
7
17
18
Payhawk
payhawk.com
 68
7
7
17
19
Chrome River
chromeriver.com
 64
6
6
16
20
Certify
certify.com
 61
6
6
15
21
Fyle
fylehq.com
 59
6
6
15
22
Mesh Payments
meshpayments.com
 60
6
6
15
23
NetSuite CRM
netsuite.com
 60
6
6
15
24
Soldo
soldo.com
 63
6
6
15
25
TravelBank
travelbank.com
 58
6
6
15
26
Happay
happay.com
 55
6
6
14
27
Moss
getmoss.com
 56
6
6
14
28
Nexonia
nexonia.com
 57
6
6
14
29
Expensya
expensya.com
 50
5
5
13
30
Teampay
teampay.co
 52
5
5
13
31
webexpenses
webexpenses.com
 53
5
5
13
32
Yokoy
yokoy.ai
 47
5
5
12
33
Mooncard
mooncard.co
 42
4
4
11
34
Center
centerexpense.com
 38
4
4
10
35
ExpenseIn
expensein.com
 32
3
3
9
36
N2F
n2f.com
 34
3
3
9
37
F
Fraedom
fraedom.com
 31
3
3
8

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 287 shared Expense Management Platforms 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 287 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 →