700M+ wallets. 27 chains. One dataset.
Every address gets a name: Binance, Aave, Jump Trading. Behavioral tags track whales, farmers, and LP providers over time. Open methodology, free to query.
01 / The Problem
0x3f5CE5FBFe3E9af3971dD833D26BA9b5C936f0bE is
a Binance hot wallet. But without labels, it looks the same as a whale accumulating ETH or a bot farming airdrops.
Is that $50M transfer going to Coinbase, Aave, or a personal wallet? Without labels, you're looking at hex strings.
Your airdrop list has 50,000 addresses. How many are sybils? How many are bots? Raw transaction data won't tell you.
A raw address doesn't tell your compliance team whether it belongs to a sanctioned entity or a market maker. Labels do.
02 / Labels vs Tags
Labels tell you what an address is. Tags tell you what it's been doing.
Static identity
A label is a persistent identifier tied to an address. It tells you the entity name (e.g. "Binance 14"), the category (CEX, DEX, DeFi), and who controls it.
Example
0x28C6... → Binance 14
Type: CEX · Subtype: Hot Wallet · Project: Binance
Behavioral & temporal
Tags describe what an address has been doing, not what it is. Each tag has a start and end date, so you can see behavior change over time. One address can have many tags at once.
Example
0x91a... → ETH Whale
Jan 2024 – Present · Also: LP Provider (Mar – Aug 2024)
03 / Coverage
All chains combined in crosschain.core.dim_labels
04 / Methodology
The full methodology is on GitHub. Most competitors keep their labeling process proprietary. Flipside's is auditable.
Scanned daily. Subgraphs are maintained by the protocols themselves (Uniswap, Aave, Compound), making them one of the most reliable sources of address identity.
Detects exchange deposit wallets, identifies whales, flags bots and airdrop farmers, and clusters related addresses. Behavioral tags refresh on a rolling 90-day window.
When a contract is created, we trace it back to its deployer. That maps the relationship between factory contracts, proxies, and the protocols that own them.
Daily pipelines pull verified labels from Etherscan and chain-native explorers. Direct protocol API integrations fill in the gaps.
Flipside's labels team runs regular QA and fixes mislabeled addresses (most commonly deposit wallets). Anyone can submit corrections through public tools.
The labeling methodology is on GitHub. You can query every label and tag for free in Data Studio. No paywall, no gated access.
05 / Use Cases
Find wallet cohorts worth rewarding. Filter by onchain behavior (active DeFi users, LP providers, governance voters) and exclude bots.
Run your address list against behavioral tags and onchain scores. Flag likely farmers and bots before you distribute tokens, not after.
See where your competitor's users came from. Which exchanges they use. Whether your users are migrating to another protocol.
Match wallet addresses to known entities. Check a user's onchain footprint across 27 chains in one query for risk assessment.
Track deposits and withdrawals between labeled CEX addresses. You see "Jump Trading deposited $12M to Coinbase," not a hex string.
Tags have date ranges. You can see when a wallet became a whale, when it started farming, or when it shifted from DeFi to NFTs.
06 / Data Access
{chain}.core.dim_labels ADDRESS Blockchain address ADDRESS_NAME Human-readable name (e.g. "Binance 14") LABEL_TYPE Category: cex, dex, defi, nft, bridge... LABEL_SUBTYPE Specific: hot_wallet, pool, deployer... PROJECT_NAME Controlling entity (e.g. "Uniswap") crosschain.core.dim_tags ADDRESS Blockchain address TAG_NAME Descriptive tag name TAG_TYPE High-level tag category START_DATE When the tag first applies END_DATE When it expires (NULL if active) Interactive SQL queries, dashboards, and exploration. Free tier available.
Natural language queries against 7T+ rows and 700M+ labeled wallets.
Direct warehouse integration for production pipelines and BI tools.
Programmatic access for applications and automated workflows.
S3, Parquet, and CSV exports for custom integrations.
07 / Why Flipside
Query any label or tag for free in Data Studio. The methodology is on GitHub. No paywall to look up an address.
400+ protocol-maintained subgraphs keep labels in sync with the protocols that own those addresses. Not guesswork.
crosschain.core.dim_labels covers all 27 chains. One query, consistent schemas. No stitching datasets together.
Combine labels with Flipside's 0-15 OnChain Scores, wallet clustering, and risk flags. Identity plus behavior in one dataset.
Get started
700M+ labeled wallets across 27 chains. Query in SQL, pull via Snowflake, or ask the AI. Open methodology, updated daily.