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ML in Production - Best practices for building real world machine learning systems — 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
actamachina.com ↗	72 match 2 shared topics	Acta Machina \| Machine Learning Blog	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
labskaramind.com ↗	70 match 2 shared topics	KaraMind Labs \| AI & Machine Learning Insights	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
aimls.org ↗	69 match 2 shared topics	Artificial Intelligence and Machine Learning Systems	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
1chipml.org ↗	69 match 2 shared topics	GitHub - 1chipML/1chipML: a library for numerical crunching and machine learning on microcontrollers · GitHub	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
laconicml.com ↗	68 match 2 shared topics	Laconicml Home \| Laconic Machine Learning	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
padme.ai ↗	68 match 2 shared topics	Edge AI platform with pre-trained machine learning models - Padmé	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
triveous.com ↗	68 match 2 shared topics	Triveous – Building Scalable AI Products for Impact	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
yusufaktan.com ↗	68 match 2 shared topics	Yusuf Aktan \| Exploring topics in data science, machine learning, backend development, and whatever else.	en	technology-and-computing	robotsllmsaihumans	emailphone	none
2rhino.com ↗	67 match 2 shared topics	2RHINO \| Creative Systems Engineering for Worldmakers	en	artificial-intelligence	robotsllmsaihumans	emailphone	partial · 8
zaagsys.com ↗	67 match 2 shared topics	AI Product Engineering Lab \| ZAAG Systems	en	artificial-intelligence WooCommerce	robotsllmsaihumans	emailphone	none
zaagxd.com ↗	67 match 2 shared topics	AI Product Engineering Lab \| ZAAG Systems	en	artificial-intelligence WooCommerce	robotsllmsaihumans	emailphone	none
acestra.com ↗	67 match 2 shared topics	Acestra :: Trigger Innovation - Data Insight, Machine Learning, Text Mining, Cloud Migration, Legacy Integration Technology Solution Provider	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
aetherflow.tech ↗	67 match 2 shared topics	AetherFlow \| AI Automation & Machine Learning Solutions	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
zakaria-narjis.com ↗	67 match 2 shared topics	Zakaria Narjis \| Machine Learning Engineer Portfolio	Germany~ en	artificial-intelligence	robotsllmsaihumans	emailphone	none
heyvaldemar.net ↗	67 match 2 shared topics	VALDEMAR \| Solutions architecture for production systems	en	technology-and-computing	robotsllmsaihumans	emailphone	none
heyvaldemar.dev ↗	67 match 2 shared topics	VALDEMAR \| Solutions architecture for production systems	en	technology-and-computing	robotsllmsaihumans	emailphone	none
rosieai.dev ↗	67 match 2 shared topics	Rosie Learning Systems \| Autonomous Crypto Intelligence	en	artificial-intelligence	robotsllmsaihumans	emailphone	partial · 8
drava.ai ↗	67 match 2 shared topics	Drava — AI Agents Built for the Real World	en	artificial-intelligence	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.