SQD On-Chain Data Indexing Project Analysis: Technical Architecture and Industry Status

According to Gate market data, as of April 8, 2026, the SQD token price is $0.03379. Its 24-hour trading volume is approximately $124,400, and its market cap is approximately $5.47 million. Compared with its historical all-time high of $0.5, the current price has fallen by more than 90%, and its cumulative decline since launch is approximately 77.47%. Behind this price trend is a data infrastructure project undergoing structural change.

In October 2025, AI business company Rezolve AI announced the acquisition of Subsquid, integrating its decentralized blockchain data platform into AI-driven business infrastructure. Rezolve AI founder and CEO Daniel M. Wagner said the acquisition aims to create a scalable enterprise AI business platform, fully leveraging Web3’s efficiency and transparency. According to publicly available information, after the acquisition is completed, the SQD token will undergo a brand makeover once regulatory approvals and exchange procedures are finalized.

From the Polkadot ecosystem to a multi-chain data layer

Subsquid was founded in 2021 and is headquartered in Zug, Switzerland. The project’s two co-founders are Marcel Fohrmann and Dmitry Zhelezov. The project was initially rooted in the Polkadot ecosystem. It developed a query engine based on the Substrate framework, and later gradually evolved into a multi-chain data indexing layer.

In terms of funding, Subsquid completed a $3.8 million seed round in November 2021, led by Hypersphere Ventures, with participation from more than 20 crypto investment institutions. In early 2024, the project conducted a community token sale on the CoinList platform, raising approximately $6.28 million, with the token sale price at $0.094. The community sale sold out in 19 minutes, setting the fastest CoinList sales record at the time. The total cumulative funding exceeded $17.5 million, and participating institutions include DFG, Zee Prime Capital, Blockchange, Lattice, and others.

Key timeline milestones are as follows: In September 2023, Subsquid launched an incentivized testnet on CoinList, attracting nearly 20,000 developers to participate in network testing. In May 2024, the native token SQD was officially issued; in June of the same year, the data lake mainnet went live. In October 2025, Rezolve AI completed its acquisition of Subsquid, marking the project’s strategic transition from an independent data infrastructure to an AI business data layer.

Technical architecture: the design logic of a modular data lake

Subsquid’s core product positioning is a decentralized data lake and query engine, providing developers with permissionless, high-performance data access. Its technical architecture uses a modular design, in contrast to the monolithic approach of traditional indexing frameworks.

Architecture layering: three modules working in coordination

Subsquid’s technical architecture can be broken down into three core modules. The first layer is the decentralized data lake layer, where distributed worker nodes store raw on-chain data, and zero-knowledge proof technology is used to ensure data integrity and security—eliminating reliance on centralized trusted intermediaries. The second layer is the real-time indexing layer, which supports indexing data even when blocks are not yet finalized, compressing latency to about 800 milliseconds. The third layer is the query engine layer, which provides developers with a TypeScript development kit through the Squid SDK, supporting custom data processing workflows and cross-chain aggregation.

Differentiated advantages: performance and cost

Compared with traditional solutions, Subsquid has significant differences in indexing speed and cost structure. Data is extracted directly from the decentralized data layer rather than being pulled from individual blockchain nodes one by one, improving indexing speed by up to 100 times compared with traditional methods. On costs, the project team stated that data extraction and indexing costs can be reduced by as much as 90%. After the mainnet goes live, the estimated cost to extract 1 TB of data is between $1 and $5. On query costs, some analysis shows the average cost per single query is approximately $0.0008, which is significantly lower than similar solutions.

At the time it was acquired, the Subsquid network had more than 2,500 active nodes, managing over 2.1 PB of blockchain data, with an average daily query volume of 5 million. The network currently supports on-chain data from more than 100 EVM and Substrate blockchains, including Ethereum and its Layer 2s, as well as the Polkadot ecosystem, and it has already entered test stages for data support on Solana and Starknet.

Tokenomics: SQD’s supply-demand mechanism and current circulation

Token supply and allocation structure

SQD is the native token of the Subsquid network, with a total supply of 1.337 billion tokens. The maximum supply is the same as the total supply. As of April 8, 2026, the circulating supply is approximately 161.4 million tokens, accounting for about 12.07% of the total. The circulating market cap is approximately $5.47 million, and the fully diluted valuation is approximately $45.35 million.

The token allocation structure is as follows: seed-round pre-investors account for 12%, seed-round investors account for 16.3%, the team accounts for 15%, the treasury accounts for 28.1%, and the remaining portion is allocated to community token sales and other uses. Tokens for early investors have a 6-month lockup period; after the TGE, 20% is released, and the remaining 80% is linearly unlocked over 24 months.

Token utility: a four-dimensional value loop

SQD tokens serve multiple functions within the ecosystem. First, as a network payment medium, the project team needs to pay SQD to purchase data query services, and approximately 70% of the collected fees are allocated to node operators as operational incentives. Second, it supports a staking incentive mechanism: both node operators and data consumers can stake tokens, and the lockup ratio has previously exceeded 35%. Third, it is used for protocol governance, with token holders participating in major decisions such as determining the direction of protocol upgrades and adding support chains. Fourth, the protocol design includes a deflationary mechanism: part of the query fees will be used to burn tokens to offset inflationary pressure.

It should be noted that the above lockup ratios, annualized returns, and other data fluctuate across different market stages. The reward mechanism in tokenomics is highly dependent on protocol revenue growth—if the query volume growth rate is lower than the token release rate, staking rewards may face the risk of decline.

Industry competitive landscape: diversification within the indexing track

The blockchain data indexing track has formed a competitive landscape with multiple players. Major participants include The Graph, Subsquid, Covalent, SubQuery, Goldsky, and others.

As a pioneer of decentralized indexing protocols, The Graph has standardized subgraph tools and a mature ecosystem, but it needs to wait for block confirmations before data can be queried, and latency is typically more than 6 seconds. Subsquid forms a differentiated advantage in terms of real-time capability by supporting immediate indexing of unconfirmed blocks, compressing latency to the millisecond level. In cross-chain capabilities, Subsquid supports cross-chain aggregated data from a single request across multiple chains such as Ethereum and Solana, while The Graph requires subgraph deployments per chain.

Covalent also focuses on multi-chain data access, emphasizing wallet application and REST API use cases. SubQuery focuses on deep support for the Polkadot and Substrate ecosystems. Different projects emphasize different aspects in real-time data processing, developer experience, and cost structure, and no single solution currently covers all application scenarios. Notably, in February 2026, The Graph released a new technology roadmap, planning to evolve from a pure indexing network into modular, multi-service data infrastructure—competition in the track is still deepening.

Boundaries of facts and market expectations

In the narrative circulating across the crypto market, there is often an information gap between what project teams advertise and what actually happens on-chain.

The project has launched its mainnet, completed multiple rounds of funding, and the token is traded on multiple exchanges. Its technical integration with Google BigQuery has been completed, allowing developers to process blockchain data using Google’s data analytics tools through the Squid SDK. Over 100 chains of data support is true, and there is verifiable publicly available information supporting the network’s node scale and data storage capacity. The Rezolve AI acquisition event has been confirmed through official announcements.

Some third-party analyses include statements such as “indexing speed improves by 100x” and “costs decrease by 90%.” These claims originate from the project team’s early promotional materials and reflect comparison results under specific test conditions. In actual production environments, differences may arise due to variables such as network scale, data complexity, and the number of concurrent requests, so they should not be taken as universally applicable conclusions. In addition, operating data such as “daily query volume exceeds 5 million” lacks independent third-party audit and verification.

After the acquisition, there is already public clarification of the SQD token’s brand makeover plan, but specific timelines and details of the new tokenomics model have not yet been disclosed. After Subsquid is integrated into Rezolve AI’s AI business platform, whether the original developer community’s independent usage scenarios will be affected by changes in commercial priorities is currently unclear.

Industry impact analysis: the AI-driven transformation of data infrastructure

Subsquid’s acquisition by Rezolve AI sends a clear signal in the crypto data infrastructure field: on-chain data indexing is evolving from an independent Web3 infrastructure layer toward an AI-economic data supply layer.

Coupling of data indexing and AI demand

In 2026, the integration of AI and blockchain technology has become increasingly mature. Decentralized data infrastructure has become a key supply source for AI training and inference. Blockchain’s immutability characteristics provide high-quality, tamper-resistant data sources for AI, while the decentralized data indexing layer enables massive amounts of on-chain data to be efficiently searched and accessed by AI systems.

Rezolve AI’s acquisition logic is built on this trend. According to its official statements, Web3 data is dispersed across decentralized networks, making it difficult to obtain the structured data AI needs. Subsquid’s decentralized data lake can aggregate, standardize, and search Web3 data, enabling AI to analyze on-chain activity and generate actionable business insights.

Demonstration effect on the indexing track

This acquisition provides a new type of exit and consolidation path for the data indexing track. Traditionally, crypto infrastructure projects create value through token listings, ecosystem expansion, and accumulating value via network effects. Meanwhile, Subsquid’s path suggests that indexing protocols with large-scale data processing capabilities may be viewed as strategic acquisition targets by AI companies or traditional data companies. If this model is proven effective, it may trigger more cross-track integration transactions and change the valuation logic and growth trajectory of data infrastructure projects.

At the same time, the acquisition also brings uncertainty. Token brand makeover involves regulatory approvals and coordination with exchanges, and existing token holders face liquidity risks during the token migration process. After integration, adjustments to commercial priorities may affect the pace and direction of the existing open-source community’s development.

Multi-scenario evolution projections

Based on current industry trends and the current state of the project, we can project three possible evolution scenarios for SQD going forward.

Scenario 1: AI integration succeeds, and token utility expands. Assuming Rezolve AI smoothly drives the brand makeover and implements the new token economics model, the SQD token would expand from a use case limited to data indexing into a foundational asset for an AI business platform, supporting multiple functions such as data access, AI inference payments, and staking-based governance. As AI agent applications grow, network query volume would increase, enabling a sustainable cycle where protocol revenue drives token burning and staking rewards. In this scenario, the token’s value-capture ability would be significantly strengthened. Prerequisites include: the acquisition and integration proceed smoothly, AI agent applications form stable data consumption demand, and the new token model gains community and regulatory recognition.

Scenario 2: The integration cycle is extended, and the project remains in a transition period. Brand makeover and the regulatory approval process continue for a long time. During the transition period, the project maintains its existing operating model but lacks major product iterations. The token price is heavily influenced by overall market sentiment and lacks an independent value-driving logic. The developer community may partially drift away amid uncertainty. Prerequisites include: a complex approval process, the team focusing its efforts on integration rather than product iteration, and the market having a vague narrative positioning for SQD.

Scenario 3: Commercial transformation dilutes the original open-source ecosystem. After the acquisition, commercial priorities shift toward serving AI enterprises, resulting in reduced investment in open-source data indexing services originally aimed at Web3 developers. Developers move to other indexing solutions, leading to a decline in network usage and protocol revenue. Staking rewards for the token weaken due to insufficient protocol revenue, further reducing holders’ willingness to participate. Prerequisites include: Rezolve AI’s insufficient ongoing investment in the open-source ecosystem, and competitors forming replacement advantages in developer experience.

Among the three scenarios, Scenario 2 has the highest probability in the short term. Brand makeover and regulatory processes usually take several months or even longer; during this period, SQD has no clear new value narrative, and its price may mainly track fluctuations in overall crypto market sentiment. Looking from the medium to long term perspective, the divergence between Scenario 1 and Scenario 3 depends on how Rezolve AI balances commercialization needs with open-source ecosystem building, and whether on-chain AI agent applications can generate sufficiently large-scale data consumption demand.

Conclusion

The blockchain data indexing track represented by SQD is at an important transformation node. Starting from the Polkadot ecosystem, Subsquid built a modular data lake and a high-performance query engine, forming differentiated competitive strengths in both technical architecture and real-time performance. However, the event of being acquired by Rezolve AI not only opens up a new narrative space for an AI business data layer, but also brings multiple uncertainties such as brand makeover, token migration, and the transitional period of the community ecosystem.

At present, the SQD token price is in a historical low range. With limited circulating market cap, price fluctuations reflect not only project-specific factors, but also a re-pricing of the data infrastructure track’s valuation amid the broader crypto market’s overall pullback. In the future, the direction of SQD’s value trajectory mainly depends on two variables: first, whether after Rezolve AI’s integration it can introduce broader real utility scenarios for the token; second, whether on-chain AI agents and data-intensive applications can form continuous, scalable data consumption demand.

Under the trend of deep integration between Web3 data infrastructure and the AI economy, SQD’s evolution path is worth continuous monitoring. Whether as a research example of data indexing technology or as an observation case of tokenomics model transition, it provides an important window for understanding structural changes in the crypto infrastructure track.