Source domain profile · Other observed source

eproxim.com in the Machine Relations Index

eproxim.com appeared as a cited source in 1 of 36,708 monitored answer runs (under 0.01%) from May 10, 2026 to November 6, 2026.

Source site Markdown Public JSON

Citation rateunder 0.01%

1 cited run of 36,708 observed answer runs.

Days cited1/174

Days with a citation, of the days observed in the current release window.

Engine breadth1

Perplexity. This is an observed-engine list, not a per-engine rate.

ConfidenceCollecting

MRI confidence is not an Answer-Source Fidelity grade.

Standing

Population ranks from the public release

Public standing: Collecting: no rank until it clears the evidence floor
Full universe: Not ranked in this release
Source role population: Not ranked in this release
Evidence-qualified source role: Not ranked in this release

Segment evidence

Observed category and question-shape rows

Segment rates use that category and question shape only. A row still collecting shows how many runs have been measured. A dash means no measured runs yet.

Category	Question shape	State	Cited runs	Observed runs	Run dates	Rate	Rank population	Badge
Fintech	How buyers choose	Published	1	230	12	0.43%	#195 of 282	Badge

Published segments: 1. Collecting segments: 0.

Citation record

One cited run

eproxim.com has been cited in one monitored answer run, on October 9, 2026, by Perplexity, in answers to Fintech / How buyers choose questions. Other sources cited for Fintech questions are on the Fintech sources page.

Peers

Nearest sources on Fintech / How buyers choose

eproxim.com holds its best segment rank, #195 of 282, in Fintech / How buyers choose, at 0.43%. 121 sources on that leaderboard share that rate, and their order inside the tie is not a measured difference. Listed here: the nearest sources cited more and less often than it, and the sources beside it that share this best segment. Full leaderboard.

Rank	Source	Source role	Segment citation rate	Against this source
#127 of 282	craftingsoftware.com	Other observed source	0.87%	+0.44 pts
#128 of 282	devopsschool.com	Other observed source	0.87%	+0.44 pts
#129 of 282	fitgap.com	Other observed source	0.87%	+0.44 pts
#130 of 282	Forbes	Editorial publication	0.87%	+0.44 pts
#131 of 282	gft.com	Other observed source	0.87%	+0.44 pts
#132 of 282	hellgate.io	Other observed source	0.87%	+0.44 pts
#191 of 282	dtnext.in	Editorial publication	0.43%	Same rate
#196 of 282	everonet.com	Vendor-owned source	0.43%	Same rate

Cite this

Citation

Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai. eproxim.com, under 0.01% citation rate, 1 of 36,708 monitored answer runs, 2026-05-10 to 2026-11-06. Release mri_score_v2.1+2026-11-06+4a9cac5e2d8d. https://machinerelations.ai/index/domains/eproxim.com. CC BY 4.0.

APA

Parrott, J. (2026). eproxim.com in the Machine Relations Index (Version mri_score_v2.1+2026-11-06+4a9cac5e2d8d) [Data set]. Machine Relations Research. https://machinerelations.ai/index/domains/eproxim.com https://doi.org/10.5281/zenodo.23652423

BibTeX

@misc{parrott2026mrieproximcom,
  author = {Parrott, Jaxon},
  title = {eproxim.com in the Machine Relations Index},
  year = {2026},
  version = {mri\_score\_v2.1+2026-11-06+4a9cac5e2d8d},
  publisher = {Machine Relations Research},
  url = {https://machinerelations.ai/index/domains/eproxim.com},
  doi = {10.5281/zenodo.23652423},
  license = {CC-BY-4.0},
  note = {Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai}
}

CITATION.cff

Release and boundary

What this profile measures

Published November 6, 2026. The observation window runs May 10, 2026 to November 6, 2026. Methodology v2.1.

Use the data

curl -fsSL "https://machinerelations.ai/data/machine-relations-index.json" -o machine-relations-index.json
curl -fsSL "https://machinerelations.ai/data/mri-release-manifest.json" -o mri-release-manifest.json
curl -fsSL "https://huggingface.co/datasets/machine-relations/machine-relations-index/resolve/main/domains.csv" -o domains.csv
curl -fsSL -L "https://doi.org/10.5281/zenodo.23652423" -o mri-zenodo.html

import json
from urllib.request import urlopen

index_url = "https://machinerelations.ai/data/machine-relations-index.json"
with urlopen(index_url) as response:
    index = json.load(response)
print(index["generated"], index["total_domains"])

The public dataset reports citation rates, rankings, and evidence counts. It excludes internal query identifiers, raw cited URLs, and answer-engine provider payloads. MRI measures observed root-domain citations in monitored prompts, not all AI answers, recommendation quality, web traffic or commercial performance. A citation is not source support.

Embed

Embed this profile’s badge

Put this badge on your site to show how often AI answers cite it. It links to this profile and updates with every new release; if a later release no longer includes this domain, the badge stops loading. To keep today’s numbers fixed, save the SVG and host it yourself.

HTML

<a href="https://machinerelations.ai/index/domains/eproxim.com"><img src="https://machinerelations.ai/index/domains/eproxim.com/badge.svg" alt="eproxim.com in the Machine Relations Index: cited in under 0.01% of monitored AI answers (1 of 36,708 runs), Nov 6, 2026 release. Machine Relations Research." width="385" height="64"></a>

Markdown

[![eproxim.com in the Machine Relations Index: cited in under 0.01% of monitored AI answers (1 of 36,708 runs), Nov 6, 2026 release. Machine Relations Research.](https://machinerelations.ai/index/domains/eproxim.com/badge.svg)](https://machinerelations.ai/index/domains/eproxim.com)