Canonical segment URLs exist only for observed category/shape pairs.
Machine Relations Index
Observed shapes6 Published1 Collecting5 ReleaseNovember 2, 2026
VC & Private Equity · Machine Relations Index category
Which sources AI engines cite for VC & Private Equity questions
Analyst and consulting research earn 59.3% of classified citations in VC & Private Equity answers (80 of 135), as of November 2, 2026.
In the November 2026 release of the Machine Relations Index, these are the sources AI answer engines cited most often for the 1 of 6 VC & Private Equity question shapes that publish a rate, each ranked on that shape's own observed runs. This category has 6 observed question-shape segments in the current public release. Each segment keeps its own observed-run denominator and dates; this page does not average rates across shapes. Observed runs are answer runs, not questions: every segment repeats a small set of distinct questions across engines and dates, so a run count is not a count of independent questions.
Top sources by question shape
The sources engines cite most, shape by shape
A rate is the share of the shape's observed answer runs that cited the source; rank is the source's place on that shape's full leaderboard.Best tools
Example pattern: best VC private equity tools. 91 observed runs across 7 dates.
| Rank | Source | Source role | Citation rate | Cited runs |
|---|---|---|---|---|
| #1 of 128 | Coyotewealth.com | Other observed source | 28.57% | 26 of 91 |
| #2 of 128 | Allocations.com | Other observed source | 27.47% | 25 of 91 |
| #3 of 128 | Vcbeast.com | Other observed source | 23.08% | 21 of 91 |
| #4 of 128 | Hebbia.com | Vendor-owned source | 20.88% | 19 of 91 |
| #5 of 128 | Ctacquisitions.com | Other observed source | 17.58% | 16 of 91 |
How buyers choose
Example pattern: how to choose VC private equity tools. Collecting observations: 90 observed runs across 6 dates against a floor of 10 runs and 7 dates, so no rate or rank is published yet.
Is it worth it
Example pattern: is VC private equity software worth it. Collecting observations: 56 observed runs across 4 dates against a floor of 10 runs and 7 dates, so no rate or rank is published yet.
Problem-first research
Example pattern: how to solve VC private equity problems. Collecting observations: 54 observed runs across 4 dates against a floor of 10 runs and 7 dates, so no rate or rank is published yet.
Top lists
Example pattern: top VC private equity platforms. Collecting observations: 49 observed runs across 3 dates against a floor of 10 runs and 7 dates, so no rate or rank is published yet.
Comparisons
Example pattern: VC private equity platform A vs B. Collecting observations: 51 observed runs across 3 dates against a floor of 10 runs and 7 dates, so no rate or rank is published yet.
Published segments met the release evidence floor.
Collecting segments expose sample progress, not mature leaderboards.
Methodology v2.1.
Question shapes
Separate denominators by segment
| Question shape | State | Observed runs | Distinct questions | Run dates | Distinct cited domains | Canonical segment |
|---|---|---|---|---|---|---|
| Best tools | Published | 91 | 7 (5 paraphrase groups) | 7 | 128 | Open leaderboard |
| How buyers choose | Collecting observations | 90 | 7 (5 paraphrase groups) | 6 | 176 | Open leaderboard |
| Is it worth it | Collecting observations | 56 | 7 (5 paraphrase groups) | 4 | 110 | Open leaderboard |
| Problem-first research | Collecting observations | 54 | 7 (5 paraphrase groups) | 4 | 138 | Open leaderboard |
| Top lists | Collecting observations | 49 | 7 (5 paraphrase groups) | 3 | 115 | Open leaderboard |
| Comparisons | Collecting observations | 51 | 7 (5 paraphrase groups) | 3 | 103 | Open leaderboard |
By answer engine
Whole-window rates on each engine
Each link ranks sources with a published VC & Private Equity segment by that source's citation rate on one engine across the whole window. It is not a rate inside VC & Private Equity alone. A collecting engine has no published ranking for this category.Cite this
Citation
Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai. VC & Private Equity, observed Machine Relations Index category, 2026-05-10 to 2026-11-02. Release mri_score_v2.1+2026-11-02+f9aaeca0db15. https://machinerelations.ai/index/categories/vc-private-equity. CC BY 4.0.APA
Parrott, J. (2026). VC & Private Equity in the Machine Relations Index (Version mri_score_v2.1+2026-11-02+f9aaeca0db15) [Data set]. Machine Relations Research. https://machinerelations.ai/index/categories/vc-private-equity https://doi.org/10.5281/zenodo.23652423BibTeX
@misc{parrott2026mrivcprivateequity,
author = {Parrott, Jaxon},
title = {VC \& Private Equity in the Machine Relations Index},
year = {2026},
version = {mri\_score\_v2.1+2026-11-02+f9aaeca0db15},
publisher = {Machine Relations Research},
url = {https://machinerelations.ai/index/categories/vc-private-equity},
doi = {10.5281/zenodo.23652423},
license = {CC-BY-4.0},
note = {Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai}
}Release and boundary
No pooled category score
Published November 2, 2026. The observation window runs May 10, 2026 to November 2, 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.htmlimport 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"])This page is a directory of observed segments. A domain's overall citation rate is not a category rate, and MRI does not publish an averaged category score in this slice.
VC & Private Equity buyers on AuthorityTech’s publication intelligence is a downstream practitioner projection of these segments. It is not source evidence, citation provenance, or an identity link for the neutral dataset.