Your feet can stay on the floor

World Liberty Financial has rolled out its USD1 stablecoin in native form on the Canton Network, positioning the token to act as the “cash leg” inside transactions that also involve tokenized real-world assets (RWAs). The move targets institutional workflows where settlement often needs to occur alongside issuance, redemption, and collateralization rather than through separate payment rails.

In a Tuesday announcement, the project said institutions can use USD1 on Canton for settlement across activities such as derivatives collateral, institutional lending, and asset issuance and redemptions. The company emphasized that native issuance is designed to let USD1 clear alongside tokenized assets within the same transaction while leveraging Canton’s privacy and permissioning controls.

Key takeaways

• USD1 is now available natively on the Canton Network, aiming to streamline settlement for tokenized real-world assets.
• The stablecoin is positioned for institutional use cases including derivatives collateral, lending, and asset issuance/redemptions.
• World Liberty says native issuance enables USD1 to settle in the same transaction as tokenized assets while using Canton’s privacy/permissioning features.
• USD1’s circulating market capitalization is about $4.05 billion, making it the sixth-largest stablecoin per DeFiLlama.
• USD1 is managed by BitGo Bank & Trust for reserve oversight and for minting/redemption processing.

Why native settlement matters for tokenized RWAs

The practical value of launching a stablecoin “natively” on a blockchain geared toward institutional finance is that it reduces the friction between tokenized assets and payment settlement. Rather than treating cash settlement as an off-chain or external step, native issuance supports the idea that stablecoin flows can occur in parallel with asset transfers, issuance events, or contract-based collateral movements.

World Liberty’s framing is that USD1 can be used for settlement where tokenized RWAs are involved—specifically as a cash leg in transactions spanning derivatives collateral and institutional lending. That matters because many tokenization efforts hinge not only on representing assets on-chain, but also on how reliably and efficiently the corresponding payment leg can be executed under the constraints institutions require.

The company also pointed to Canton’s privacy and permissioning controls. For investors and institutions evaluating tokenized asset infrastructure, these features are often central: they can determine what data is visible, who can interact with what components, and how compliance-oriented workflows are structured within blockchain systems.

USD1’s current scale and who operates it

USD1 has a market capitalization of about $4.05 billion, according to DeFiLlama stablecoin data, where the token is described as the sixth-largest stablecoin by market cap. In terms of issuer and operations, World Liberty said USD1 is issued by BitGo Bank & Trust, which manages reserves and handles the minting and redemption process.

That operational separation—stablecoin reserve management and issuance processing handled by a named bank entity, while on-chain usage is enabled through a network integration—underscores how the stablecoin business model often blends traditional treasury controls with blockchain distribution. For participants on Canton, this structure can affect assumptions around redemption processes and reserve oversight, especially when stablecoin settlement is intended for regulated or institutional settings.

Canton’s institutional focus and the network’s tokenized-asset activity

Canton positions itself as a public, permissionless blockchain designed for institutional finance, and the company says it handles large volumes of tokenized asset movement. In the update accompanying the USD1 integration, Canton claimed it processes and issues more than $9 trillion in tokenized assets each month. It also cited more than $350 billion in onchain US Treasurys moving across the network daily.

Those figures are not direct guarantees about future USD1 usage on Canton, but they do help contextualize why a stablecoin integration is strategically meaningful. If tokenized securities and RWA instruments are already being transferred with significant frequency, the settlement layer becomes a key bottleneck—or a competitive advantage—depending on how efficiently it can match payment timing and compliance requirements.

By placing USD1 into that environment, World Liberty appears to be aiming for deeper integration with institutional token flows rather than limiting USD1 to a standalone stablecoin role within broader DeFi markets.

Integration timing: part of a wider push on Canton

The USD1 launch follows another expansion announcement for Canton reported last week. According to the earlier coverage, Digital Asset and former US House Speaker Paul Ryan’s American Idea Foundation unveiled plans to pilot a Canton-based system for distributing state-administered benefits across three US states, with an anticipated start in 2027.

While the USD1 initiative and the benefits distribution pilot are clearly different in purpose, they both point to Canton’s broader ambition: attracting enterprise-grade use cases and institutional participants. For observers, the sequence is important because it suggests the network is actively positioning its rails for multiple categories of on-chain activity—ranging from financial settlements involving tokenized assets to non-traditional public distribution workflows.

What to watch next for USD1 on Canton

With USD1 now live natively on Canton, the key question for market participants is how quickly institutions move from testing to sustained on-chain settlement for tokenized asset transactions. Watch for evidence of USD1 being used in the specific workflows World Liberty highlighted—especially collateral and issuance/redemption flows—as that will indicate whether native settlement delivers measurable operational advantages in real transactions.

SQD has added validated data from 10 blockchain networks to Google Cloud’s BigQuery platform, giving developers and companies access to full chain histories checked through six cryptographic tests.

SQD brings validated blockchain data into BigQuery

SQD said in an Aug. 24 announcement that its enterprise arm, SQD 360, is providing the indexing system and data pipelines behind datasets available through Google Cloud Web3 Blockchain Analytics.

The initial contribution covers 10 networks from their genesis blocks, allowing analysts to examine their complete available histories rather than records collected only after the integration began. SQD did not identify all 10 chains in its announcement or provide a timetable for adding the next group.

Before the information reaches BigQuery, SQD said each block passes six cryptographic checks. The process includes comparing data from multiple sources and checking transaction roots and state roots, which are cryptographic values used to confirm whether a block’s records match the underlying blockchain state.

SQD said the checks are intended to catch missing, incorrect, or inconsistent records before they enter analytics pipelines. Fresh blocks must also pass the validation process as the datasets continue to update.

Once loaded into BigQuery, the records become available through the same cloud environment used for business intelligence, machine learning, and large-scale data analysis. Developers can therefore examine blockchain activity without building an indexer, storing an entire chain history, or maintaining separate infrastructure for each network.

“Partnering with Google Cloud Web3 to bring our validated data standard to BigQuery is a defining step for SQD, and a strong signal that enterprise-grade blockchain data has arrived,” SQD CEO Wanja Oberhof said.

The companies did not disclose financial terms, revenue-sharing arrangements, or service-level commitments tied specifically to the partnership.

SQD Network distributes storage and query work

SQD operates a decentralized data network built to collect, verify, store and serve information generated by blockchains and Web3 applications. Its infrastructure separates the work among data providers, independent worker nodes, and gateways rather than relying on one central database.

According to SQD Network documentation, data providers submit blockchain records before a scheduler assigns pieces of each dataset to worker nodes. Workers supply storage and computing resources, hold copies of the assigned records, and answer queries submitted through gateways.

Each worker must bond 100,000 SQD tokens to register on the network. Workers receive token rewards based on factors such as uptime, the amount of data served, and delegated tokens, while provable violations of network rules can lead to penalties.

Gateways provide the connection between data consumers and the worker network. The amount of SQD locked by a gateway operator determines how many requests it can send, tying query capacity to the network’s token-based resource system.

SQD says its full data service covers more than 130 networks, although only 10 are included in the first Google Cloud contribution described in the announcement. Its Portal product offers historical and real-time information from chains across the Ethereum Virtual Machine, Solana, Substrate, and Bitcoin-based ecosystems.

Unlike a standard blockchain node, which may provide raw or recent network information, SQD’s system converts records into structured datasets containing blocks, transactions, logs, traces and changes in blockchain state. Structured records allow analysts to search large periods and compare activity without processing raw chain files each time.

Google Cloud expands access to indexed onchain records

Google Cloud describes Blockchain Analytics as a service that places indexed blockchain information in BigQuery for analysis through SQL, a common language for searching and organizing databases. The product lets users query blocks, transactions, event logs, and call traces without operating nodes or creating an indexer for every protocol.

BigQuery can also combine onchain records with a company’s internal data. A wallet service, for example, could compare blockchain transactions with activity recorded inside its application, while a compliance team could build searches for transfers involving specified addresses. The accuracy of any resulting report would still depend on the query design, address labels, and other data added by the user.

Google Cloud began placing blockchain records in BigQuery in 2018 with Bitcoin and later added Ethereum and other networks. In 2023, the company added 11 blockchain datasets, including Avalanche, Arbitrum, Optimism, Polygon, Polkadot, and Tron.

The SQD arrangement follows other efforts to connect decentralized data sources with cloud services. In July 2025, crypto.news covered OORT’s dataset listing on Google Cloud Analytics Hub and several other enterprise marketplaces. OORT’s offering contained 100,000 user-contributed data points, with their contributions recorded onchain to help users check the source and structure of the information.

Google Cloud has also built services that give applications direct access to blockchain networks. In September 2024, it launched an Ethereum RPC that initially supported the Ethereum mainnet and test networks. The preview offered a free tier of up to 100 requests per second and one million requests per day.

The RPC service and BigQuery datasets serve different tasks. RPC endpoints allow applications to request current blockchain information and submit transactions, while indexed datasets are designed for searches across large amounts of historical data.

BigQuery data supports enterprise and agent-based analysis

For U.S. developers and companies already using Google Cloud, the integration places SQD-supplied records inside a familiar analytics service rather than requiring a separate blockchain-data system. Google’s documentation says users can reach public datasets through the Cloud console, command-line tools or the BigQuery API.

Google pays the storage costs for datasets included in its Public Dataset Program, while users pay for the queries they run. The first one terabyte of query processing each month is free under Google Cloud’s current pricing structure, although access can be limited by an organization’s own security controls.

Dataset location also matters for American users, with internal policies governing where information is processed. Google says every public dataset has an assigned region, while its BigQuery sample tables are held in the U.S. multi-region. SQD’s announcement did not specify the storage location for each contributed blockchain dataset.

Agent-based access forms another part of the planned work. In May, earlier coverage reported that Solana Foundation and Google Cloud launched Pay.sh, which lets AI agents pay for APIs with stablecoins and supports services including BigQuery, Gemini and Vertex AI.

Under the SQD roadmap, additional agent functions could allow automated software to retrieve and analyze verified blockchain records inside Google Cloud. SQD did not explain which functions will be released, which AI systems will support them, or when they will become available.

More blockchain networks are also due to join the integration, according to the announcement. SQD has not named the next chains, disclosed how they will be selected, or provided a release schedule.