Allbridge Core allows users to send stablecoins from one chain to another almost immediately by using native liquidity pools deployed across 5 EVM and non-EVM blockchains. Liquidity providers receive the majority of transfer fees paid by users (supply-side fees).

Allbridge Core is a cross-chain stablecoin bridge. Allbridge Core was co-founded by Yuriy Savchenko and Andriy Velykyy, and was launched in September 2022.

The Allbridge team own and govern the protocol. They currently take a cut of the transfer fees paid by the users (revenue). Allbridge Core’s investors include Race Capital and others.

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Allbridge Core

# Allbridge Core Active users (monthly) Methodology

## 1. Overview

Monthly Active Users (MAU) for Allbridge measures the number of unique users who interact with the Allbridge cross-chain bridge protocol within a rolling 30-day window. This metric captures user engagement across multiple blockchain networks and provides insights into the protocol's adoption and usage patterns. The calculation uses HyperLogLog approximation for efficient processing of large user datasets and provides breakdowns across different dimensions including chains, user types, and products.

## 2. Data sources

The MAU calculation relies on the following raw blockchain data sources:

- **Allbridge bridge events**: Parsed `TokensSent` and `TokensReceived` events from Allbridge v1 and Bridge2 contracts across BSC, Ethereum, and Polygon blockchains
- **Cross-chain transaction data**: Bridge transaction events that capture both token sending and receiving operations
- **User identification data**: Recipient addresses and message data from bridge events that identify unique users
- **Chain metadata**: Origin chain identification data embedded in cross-chain messages to handle non-EVM chains like Solana and Tron

## 3. Step-by-step calculation

### Component A: User identification from bridge events
- **Purpose**: Extracts unique user addresses from all Allbridge bridge interactions across supported chains
- **Logic**: Processes both `TokensSent` and `TokensReceived` events from Allbridge v1 and Bridge2 contracts on BSC, Ethereum, and Polygon. For `TokensSent` events, extracts the `recipient` field directly as the user address. For `TokensReceived` events, extracts user addresses from the message data and applies special handling for non-EVM chains by parsing the origin chain ID from the message field and only including transactions from Solana (chain ID 3) and Tron (chain ID 4) to prevent double-counting with EVM chain events
- **Key fields**: `recipient` addresses from bridge events, `block_timestamp` for temporal analysis, `transaction_hash` for deduplication, `chain` for multi-chain analysis, and `user_type` classified as "Trader"

### Component B: Daily active user aggregation  
- **Purpose**: Aggregates unique users by day with dimensional breakdowns
- **Logic**: Groups the user events by daily timestamp boundaries using timestamp truncation, along with dimensions including chain, user type, and product ID. Creates distinct user counts per day while preserving dimensional attributes for downstream analysis
- **Key fields**: Daily `timestamp` boundaries, `chain` identifiers, `user_type` classifications, `product_id` for product-level analysis, and `user_address` for unique user identification

### Component C: HyperLogLog sketch creation
- **Purpose**: Converts daily user sets into HyperLogLog sketches for efficient approximate distinct counting
- **Logic**: Takes the daily aggregated user data and initializes HyperLogLog sketches with precision parameter 15 for each combination of day, chain, user type, and product. This enables scalable approximate counting of unique users across large datasets while maintaining dimensional granularity
- **Key fields**: HyperLogLog `hll` sketches initialized from daily user sets, maintaining all dimensional attributes for downstream merging operations

### Component D: Rolling window construction
- **Purpose**: Creates 30-day rolling windows for MAU calculation using a datespine approach
- **Logic**: Generates a complete datespine covering the entire date range from the earliest data to yesterday, then creates join relationships between each target date and the 30 days leading up to it (including the target date). This ensures consistent MAU calculation even when certain days have no user activity, as the datespine provides complete temporal coverage
- **Key fields**: Target `timestamp` for MAU calculation, `joinday` timestamps representing each day in the 30-day window, enabling comprehensive temporal joins

### Component E: HyperLogLog merging for MAU calculation
- **Purpose**: Merges HyperLogLog sketches across 30-day windows to calculate approximate MAU
- **Logic**: For each target date, joins the rolling window structure with the daily HyperLogLog sketches to collect all relevant sketches from the 30-day period. Merges the HyperLogLog sketches using the merge_partial function and extracts the final approximate distinct count using hll_count.extract. This process is performed separately for each dimensional breakdown
- **Key fields**: Merged `hll` sketches representing unique users over 30-day periods, extracted `user_mau` counts as the final metric values

### Component F: Dimensional breakdown creation
- **Purpose**: Generates MAU calculations across multiple analytical dimensions
- **Logic**: Creates separate MAU calculations for four different dimensional levels: project-level (overall Allbridge MAU), chain-level (MAU by individual blockchain), user-type-level (MAU by user classification), and product-level (MAU by specific products). Each breakdown uses the same HyperLogLog merging logic but groups by different dimensional combinations, with non-relevant dimensions set to null
- **Key fields**: `dimensions` field indicating the breakdown type, relevant dimensional fields (`chain_id`, `user_type`, `product_id`), and calculated `user_mau` values for each dimensional combination

### Final aggregation
- **Combining components**: Unions all dimensional breakdowns (project-level, chain-level, user-type-level, and product-level) into a single result set, creating a comprehensive view of MAU across different analytical perspectives
- **Currency conversion**: Not applicable for user count metrics
- **Time aggregation**: Uses rolling 30-day windows calculated daily, providing continuous MAU updates without traditional monthly boundaries
- **Final calculation**: The final MAU value represents the approximate count of unique users who interacted with Allbridge within any rolling 30-day period, calculated using HyperLogLog approximation and presented across multiple dimensional breakdowns for comprehensive analysis

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

Unique revenue-generating users over a rolling 30-day window.

Allbridge Core

Active users (monthly)

Active users (monthly)

Competitive landscape

Chain breakdown