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CoinGlass | Crypto Market Data: Derivatives, Options, Spot, Order Flow, Liquidity & Order Depth, Liquidation Heatmaps — 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 Financial Industry →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
123chill.com ↗	100 match 1 shared topics	CoinGlass \| Crypto Market Data: Derivatives, Options, Spot, Order Flow, Liquidity & Order Depth, Liquidation Heatmaps	en	financial-industry	robotsllmsaihumans	emailphone	none
luramic.com ↗	67 match 1 shared topics	Luramic – Global Market Access & Liquidity Provider	en	financial-industry	robotsllmsaihumans	emailphone	none
cryptosmc.com ↗	66 match 1 shared topics	CryptoSMC - Institutional Charting & Order Flow \| Smart Money Concepts	en	financial-industry	robotsllmsaihumans	emailphone	none
implieddata.com ↗	66 match 1 shared topics	ImpliedData — Prediction Market Datasets	en	financial-industry	robotsllmsaihumans	emailphone	partial · 8
cryptomarketmaking.io ↗	66 match 1 shared topics	Crypto Market Making Explained – How It Works in 2025	en	financial-industry	robotsllmsaihumans	emailphone	none
mddl.org ↗	66 match 1 shared topics	MDDL • Market Data Definition Language	United States~ en	financial-industry WordPress	robotsllmsaihumans	emailphone	none
acrossthespread.store ↗	65 match 1 shared topics	Across The Spread – Asia global macro market insights by Weston Nakamura, a Tokyo-based former derivatives trader and financial content creator known for Market Depth podcast on Blockworks Macro and Real Vision.	en	financial-industry WordPress WooCommerce	robotsllmsaihumans	emailphone	full · 12
blocksurety.com ↗	65 match 1 shared topics	Asset Tokenization for Liquidity & Investment \| Block Surety	en	financial-industry WordPress WooCommerce	robotsllmsaihumans	emailphone	none
acikenya.co.ke ↗	65 match 1 shared topics	ACI Kenya – Financial Markets Association	en	financial-industry	robotsllmsaihumans	email phone	none
cryptovalley.swiss ↗	65 match 1 shared topics	Home - Crypto Valley Association	en	financial-industry WordPress	robotsllmsaihumans	emailphone	none
anchorage.com ↗	65 match 1 shared topics	Crypto Bank for Institutions \| Anchorage Digital	United States~ en	financial-industry	robots llmsaihumans	emailphone	none
corvil.com ↗	65 match 1 shared topics	Pico: Trading Infrastructure, Market Data & Analytics	United States~ en	financial-industry Statamic	robotsllmsaihumans	emailphone	none
lupomarkets.com ↗	65 match 1 shared topics	Lupo Market Frameworks	en	financial-industry WordPress	robotsllmsaihumans	emailphone	none
mcapmarkets.com ↗	65 match 1 shared topics	MCAP \| Advanced Market Solutions for Global Trading	en	financial-industry	robotsllmsaihumans	emailphone	none
avalonfinance.xyz ↗	65 match 1 shared topics	Avalon Labs: Institutional Bitcoin Credit & Liquidity	en	financial-industry	robotsllmsaihumans	emailphone	none
blackmountainsolution.com ↗	64 match 1 shared topics	BlackMountain Solutions - Institutional Crypto Advisory	en	financial-industry	robotsllmsaihumans	emailphone	none
baessolutions.com ↗	64 match 1 shared topics	BAES Solutions — Quantitative Investment Technology & Advisory	en	financial-industry	robotsllmsaihumans	emailphone	none
0hub.com ↗	64 match 1 shared topics	Zerohub — crypto exchange and processing solutions	en	financial-industry	robotsllmsaihumans	email phone	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.