---
title: "hellorayo.co.uk in the Machine Relations Index"
description: "Canonical domain: hellorayo.co.uk"
canonical: "https://machinerelations.ai/index/domains/hellorayo.co.uk"
---

# hellorayo.co.uk in the Machine Relations Index

Canonical URL: https://machinerelations.ai/index/domains/hellorayo.co.uk
Canonical domain: hellorayo.co.uk
Source role: Editorial publication
Release mri_score_v2.1+2026-11-07+296ae2caa083; methodology mri_score_v2.1; generated 2026-11-07; window 2026-05-10 to 2026-11-07; artifact 51fa53f555d2.

hellorayo.co.uk appeared as a cited source in 1 of 37,140 monitored answer runs (under 0.01%) from 2026-05-10 to 2026-11-07.

## How the Site Describes Itself

> Say hello to Rayo! Discover your favourite radio stations and podcasts all in one place.

hellorayo.co.uk describes itself this way in the description tag on its homepage, read on November 7, 2026. It is the source's own wording, quoted as found, not a finding of this Index.

## Overall Evidence

- Citation rate: under 0.01%
- Cited runs: 1 of 37,140
- Days cited: 1 of 175
- Engine breadth: 1 observed engine (perplexity)
- Confidence: Collecting
- Standing: Collecting: no rank until it clears the evidence floor

## Observed Segments

| Category | Question shape | State | Cited runs | Observed runs | Run dates | Rate | Standing |
|---|---|---|---:|---:|---:|---:|---|
| [Cybersecurity](https://machinerelations.ai/index/categories/cybersecurity) | [Problem-first research](https://machinerelations.ai/index/categories/cybersecurity/problem_first) | published | 1 | 287 | 13 | 0.35% | #316 of 436 |

## Citation Record

hellorayo.co.uk has been cited in one monitored answer run, on October 6, 2026, by Perplexity, in answers to Cybersecurity / Problem-first research questions. Other sources cited for Cybersecurity questions: https://machinerelations.ai/index/categories/cybersecurity

## Peers

hellorayo.co.uk holds its best segment rank, #316 of 436, in Cybersecurity / Problem-first research, at 0.35%. 204 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. Leaderboard: https://machinerelations.ai/index/categories/cybersecurity/problem_first

| Rank | Source | Source role | Segment citation rate | Against this source |
|---|---|---|---:|---|
| #181 of 436 | [hypr.com](https://machinerelations.ai/index/domains/hypr.com) | Other observed source | 0.70% | +0.35 pts |
| #182 of 436 | [incident.io](https://machinerelations.ai/index/domains/incident.io) | Other observed source | 0.70% | +0.35 pts |
| #183 of 436 | [israeldefense.co.il](https://machinerelations.ai/index/domains/israeldefense.co.il) | Other observed source | 0.70% | +0.35 pts |
| #184 of 436 | [itbrief.co.uk](https://machinerelations.ai/index/domains/itbrief.co.uk) | Vendor-owned source | 0.70% | +0.35 pts |
| #185 of 436 | [itechguides.com](https://machinerelations.ai/index/domains/itechguides.com) | Market and company database | 0.70% | +0.35 pts |
| #186 of 436 | [kaseya.com](https://machinerelations.ai/index/domains/kaseya.com) | Other observed source | 0.70% | +0.35 pts |
| #315 of 436 | [heise.de](https://machinerelations.ai/index/domains/heise.de) | Other observed source | 0.35% | Same rate |
| #322 of 436 | [hyperping.com](https://machinerelations.ai/index/domains/hyperping.com) | Other observed source | 0.35% | Same rate |

## Citation

Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai. hellorayo.co.uk, under 0.01% citation rate, 1 of 37,140 monitored answer runs, 2026-05-10 to 2026-11-07. Release mri_score_v2.1+2026-11-07+296ae2caa083. https://machinerelations.ai/index/domains/hellorayo.co.uk. CC BY 4.0.

APA

Parrott, J. (2026). hellorayo.co.uk in the Machine Relations Index (Version mri_score_v2.1+2026-11-07+296ae2caa083) [Data set]. Machine Relations Research. https://machinerelations.ai/index/domains/hellorayo.co.uk https://doi.org/10.5281/zenodo.23652423

BibTeX

```bibtex
@misc{parrott2026mrihellorayocouk,
  author = {Parrott, Jaxon},
  title = {hellorayo.co.uk in the Machine Relations Index},
  year = {2026},
  version = {mri\_score\_v2.1+2026-11-07+296ae2caa083},
  publisher = {Machine Relations Research},
  url = {https://machinerelations.ai/index/domains/hellorayo.co.uk},
  doi = {10.5281/zenodo.23652423},
  license = {CC-BY-4.0},
  note = {Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai}
}
```

DOI: https://doi.org/10.5281/zenodo.23652423

Citation file: https://machinerelations.ai/CITATION.cff

## Badge

Badge image: https://machinerelations.ai/index/domains/hellorayo.co.uk/badge.svg

[![hellorayo.co.uk in the Machine Relations Index: cited in under 0.01% of monitored AI answers (1 of 37,140 runs), Nov 7, 2026 release. Machine Relations Research.](https://machinerelations.ai/index/domains/hellorayo.co.uk/badge.svg)](https://machinerelations.ai/index/domains/hellorayo.co.uk)

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.

## Use the data

The public JSON is https://machinerelations.ai/data/machine-relations-index.json. The release manifest is https://machinerelations.ai/data/mri-release-manifest.json. The domain CSV is https://huggingface.co/datasets/machine-relations/machine-relations-index/resolve/main/domains.csv. The Zenodo concept DOI is https://doi.org/10.5281/zenodo.23652423.

```bash
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
```

```python
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"])
```

## Public Boundary

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; it does not measure all AI answers, recommendation quality, website traffic, or commercial performance. A citation does not prove source support, and MRI confidence is not an Answer-Source Fidelity grade.

## Related Sources

- [Machine Relations Index](https://machinerelations.ai/index)
- [Public JSON artifact](https://machinerelations.ai/data/machine-relations-index.json)
- [Release manifest](https://machinerelations.ai/data/mri-release-manifest.json)