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Steffen D. Sommer | Technical leader from Copenhagen, Denmark — 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 Executive Leadership And Management →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
mccune.dev ↗	69 match 2 shared topics	Brian McCune - Technology Leader \| Brian McCune	en	executive-leadership-and-management	robotsllmsaihumans	emailphone	none
aaronkinder.com ↗	69 match 2 shared topics	Aaron Kinder \| Technology Leader & MSP Strategist	en	technology-industry	robotsllmsaihumans	email phone	none
aisafetyimplementation.com ↗	69 match 2 shared topics	Built for Complexity — Technical Project & Program Leader	en	executive-leadership-and-management	robotsllmsaihumans	emailphone	none
kartik.nyc ↗	68 match 2 shared topics	Kartik Shankar \| Technology Leader & Engineering Executive	en	technology-industry	robotsllmsaihumans	emailphone	none
alessandrofrancia.link ↗	68 match 2 shared topics	Alessandro Francia — Technical Project Manager	en	technology-industry	robotsllmsaihumans	email phone	partial · 8
adnanahmad.xyz ↗	68 match 2 shared topics	Adnan Ahmad - Fractional CTO for Scale-ups \| Technical Leadership & Strategy	en	executive-leadership-and-management	robotsllmsaihumans	emailphone	none
cwright.tech ↗	67 match 2 shared topics	Christopher Wright — Senior Technical Product Manager	en	executive-leadership-and-management	robotsllmsaihumans	emailphone	none
narathota.com ↗	67 match 2 shared topics	Kavindu Narathota — Principal Technical Product & Program Leader \| Lead Software Engineer & Advisor	en	executive-leadership-and-management	robotsllmsaihumans	emailphone	none
richardbekhazi.com ↗	67 match 2 shared topics	Richard Bekhazi \| Technical Program Leader	en	executive-leadership-and-management	robotsllmsaihumans	emailphone	none
akashshukla.org ↗	67 match 2 shared topics	Akash Shukla - Technology & Business Leader \| Akash Shukla	en	technology-industry	robotsllmsaihumans	emailphone	none
mjconnection.com ↗	67 match 2 shared topics	Michael Johnson \| Technology Leadership & Advisory	en	technology-industry	robotsllmsaihumans	emailphone	none
zsstor.com ↗	67 match 2 shared topics	Zack Stor \| Technology Leadership & Strategy	en	technology-industry	robotsllmsaihumans	emailphone	none
deborahfisk.com ↗	67 match 2 shared topics	deborahfisk – Leadership – Technology – Creativity	en	executive-leadership-and-management WordPress	robotsllmsaihumans	emailphone	none
kenstowell.work ↗	66 match 2 shared topics	Ken Stowell - Engineering Leader & CTO	en	executive-leadership-and-management	robotsllmsaihumans	emailphone	none
dennismende.com ↗	66 match 2 shared topics	Dennis Mende \| Senior Technology Leader & Strategy Executive	en	executive-leadership-and-management Sanity	robotsllmsaihumans	emailphone	none
ahmedhosny.dev ↗	66 match 2 shared topics	Dr. Ahmed Hosny Ibrahim — Fractional CTO & Technology Director \| MENA Engineering Leadership	Egypt~ en	technology-industry	robots llmsaihumans	emailphone	none
adrianmoreno.info ↗	66 match 2 shared topics	Adrián Moreno Peña \| VP of Technology @ Worksome ⸱ Product & Engineering Leader (Copenhagen)	en	executive-leadership-and-management Spree Commerce	robotsllmsaihumans	email phone	none
mockletdesign.com ↗	66 match 2 shared topics	Rodney Tupai \| Technology Product Executive	en	technology-industry	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.