Overview Leaderboard Methodology
Industry Report

Invoice and Receipt Capture Tools

Tools that use OCR and mobile capture to digitize receipts and invoices, automate data extraction, and route documents for reimbursement or accounting.

Brands tracked: 37
Brands analyzed: 37
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 287
Total responses: 1,470
Top Brand Overall?
Expensify
78/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Microsoft
92

Highest score on the LBA metric.

Authority Leader?
Expensify
73

Highest score on the Authority metric.

TOM Leader?
Expensify
82

Highest score on the TOM metric.

Expensify leads the Invoice and Receipt Capture Tools category in AI responses

Expensify is the most consistently-surfaced brand when users ask AI assistants about Invoice and Receipt Capture Tools, but not to the point of monopolising the conversation. Dext 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 37 Invoice and Receipt Capture Tools 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
Expensify
expensify.com
 78
73
82
78
2
Dext
dext.com
 75
43
76
62
3
Zoho
zoho.com
 74
34
56
52
4
SAP Concur
concur.com
 74
19
34
36
5
Microsoft
microsoft.com
 92
8
47
32
6
Xero
xero.com
 82
12
29
31
7
Adobe
adobe.com
 66
5
54
27
8
BILL
bill.com
 81
12
20
27
9
Hubdoc
hubdoc.com
 73
9
25
26
10
Ramp
ramp.com
 87
16
14
26
11
Shoeboxed
shoeboxed.com
 67
4
38
22
12
Rossum
rossum.ai
 73
12
11
21
13
ABBYY
abbyy.com
 83
8
12
20
14
Rydoo
rydoo.com
 61
4
8
13
15
Wave
waveapps.com
 51
5
6
12
16
Tipalti
tipalti.com
 69
1
12
10
17
Veryfi
veryfi.com
 67
3
5
10
18
Brex
brex.com
 71
0
7
2
19
AutoEntry
autoentry.com
 69
0
4
1
20
Certify
certify.com
 43
0
1
1
21
Klippa
klippa.com
 52
0
1
1
22
Pleo
pleo.io
 69
0
1
1
23
Abacus
abacus.com
 18
0
0
0
24
Capture Expense
captureexpense.com
 20
0
0
0
25
Corpay One
corpayone.com
 43
0
0
0
26
Datamolino
datamolino.com
 42
0
0
0
27
Docyt
docyt.com
 32
0
0
0
28
Envoice
envoice.eu
 16
0
0
0
29
E
EzzyBills
ezzybills.com.au
 22
0
0
0
30
Fyle
fylehq.com
 57
0
0
0
31
M
MMC Receipt
mmcreceipt.com
 0
0
0
0
32
N2F
n2f.com
 41
0
0
0
33
Neat
neat.com
 58
0
0
0
34
QuickBooks Live
intuit.com
 72
0
0
0
35
SparkReceipt
sparkreceipt.com
 15
0
0
0
36
Tallie
tallie.com
 24
0
0
0
37
Yokoy
yokoy.ai
 54
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 287 shared Invoice and Receipt Capture Tools 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 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 →