similar sites

Browse

AI Report Tools

Sites similar to sanealytics.com

Sanealytics alternatives & similar sites

sane.a.lytics – finding meaning in data — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Artificial Intelligence →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
swimmingindata.io ↗	68 match 2 shared topics	Swimming in data	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
nathanielborenstein.com ↗	65 match 2 shared topics	The Hopeful Cyborg – An Internet greybeard finding hope in a shared future with intelligent machines.	en	technology-and-computing WordPress	robotsllmsaihumans	emailphone	none
distilligent.ai ↗	65 match 2 shared topics	Distilligent — The meaning between the data	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
distilligent.net ↗	65 match 2 shared topics	Distilligent — The meaning between the data	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
decodeanalytics.blog ↗	65 match 2 shared topics	Decode Analytics – Sharing worthy updates from data analytics and AI. Occasionally suggest company to invest.	en	technology-and-computing WordPress	robotsllmsaihumans	emailphone	none
descriptdata.com ↗	64 match 2 shared topics	Descript data	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
avandeursen.com ↗	64 match 2 shared topics	Arie van Deursen \| Software engineering in theory and practice	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
fayazlabs.com ↗	64 match 2 shared topics	Fayaz Labs — Building Intelligent Systems	en	artificial-intelligence	robotsllmsaihumans	emailphone	partial · 8
swimminginai.com ↗	64 match 2 shared topics	Swimming in AI	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
haskelabs.com ↗	64 match 2 shared topics	Haske Labs — Illuminating Ideas. Building Futures.	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
axiomdatalab.com ↗	64 match 2 shared topics	Axiom Data Lab \| ML Systems, Analytics & Decision Infrastructure	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
dekings.dev ↗	64 match 2 shared topics	data science and analytics engineering, how to, machine and deep learning	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
sanzgiri.com ↗	64 match 2 shared topics	Ashutosh Sanzgiri’s Fastpages Blog \| Musings on Data Science and Machine Learning	en	technology-and-computing	robotsllmsaihumans	emailphone	none
dirtydata.earth ↗	64 match 2 shared topics	Dirty Data	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
designed-analytics.com ↗	64 match 2 shared topics	Designed Analytics Blog – Real World Solutions	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
lucenthq.com ↗	64 match 2 shared topics	AI Session Replay Tool for Finding Bugs Users Hit \| Lucent	en	technology-and-computing Reaction Commerce	robots llmsaihumans	emailphone	none
narayanipatil.com ↗	64 match 2 shared topics	Narayani Patil \| Data Engineer	en	technology-and-computing	robotsllmsaihumans	emailphone	none
data-stories.co.uk ↗	64 match 2 shared topics	Data Stories – Engaging with data in a post-truth environment	GB en	artificial-intelligence WordPress WooCommerce	robotsllmsaihumans	emailphone	none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.