Chromia on-chain vector database: A new chapter in the fusion of Blockchain and AI

Key Overview

• On-chain Vector Infrastructure: Chromia has launched an on-chain vector database based on PostgreSQL, marking an important advancement in the practical integration of AI and blockchain.

• Cost-effectiveness and Development Convenience: Chromia provides a blockchain integration environment that is 57% cheaper than traditional vector solutions, lowering the development threshold for AI-Web3 applications.

• Future Plans: The platform plans to expand EVM indexing, AI inference capabilities, and developer ecosystem support, aiming to become a leader in AI innovation in the Web3 space.

1. The Current Status of AI and Blockchain Integration

The combination of AI and Blockchain has always been a focal point of industry attention. Centralized AI systems face challenges such as transparency, reliability, and cost predictability, which are areas where Blockchain may provide solutions.

Despite the recent explosive growth of the AI agent market, most projects have only achieved superficial integration of two technologies. Many projects rely on the speculative frenzy of cryptocurrencies to gain funding and exposure, rather than deeply exploring the technical or functional synergies with Web3. As a result, the valuations of numerous projects have significantly declined from their peaks.

The fundamental reason why AI and Blockchain are difficult to truly integrate lies in several structural challenges, among which the most prominent is the complexity of on-chain data processing. Data remains fragmented, and the technology is highly volatile. If data access and utilization could be as simple as in traditional systems, the industry might have already achieved more definitive results.

This dilemma is similar to the lack of a common language or true intersection between two powerful technologies from different fields. The industry increasingly needs an infrastructure that can bridge the gap, leveraging the strengths of both AI and Blockchain, while also serving as a point of convergence for both.

Addressing this challenge requires a system that is both cost-effective and high-performance, in order to match the reliability of existing centralized tools. In this context, the vector database technology that supports most of today's AI innovations is becoming a key enabler.

2. The Necessity of Vector Databases

With the widespread application of AI, vector databases have emerged due to their ability to overcome the limitations of traditional database systems. These databases convert complex data such as text, images, and audio into "vector" form for storage. Because they retrieve data based on similarity rather than exact matches, vector databases are more aligned with AI's understanding of language and context than traditional databases.

Traditional databases are like library catalogs, returning only books that contain specific words, while vector databases can present related conceptual content. This is thanks to the system storing information in numerical vector form, capturing relationships based on conceptual similarity rather than exact words.

For example, in a conversation: when asked "How do you feel today?", the response "The sky is particularly clear" allows us to understand the positive emotion, even without using explicit emotional vocabulary. Vector databases operate in a similar way, enabling systems to interpret underlying meanings rather than relying solely on direct word matching. This simulates human cognitive patterns, achieving more natural and intelligent AI interactions.

In the Web2 domain, the value of vector databases has been widely recognized, and multiple platforms have received substantial investments. In contrast, Web3 has struggled to develop comparable solutions, leaving the integration of AI and Blockchain largely at a theoretical level.

3. The Vision of Chromia on-chain Vector Database

Chromia, as a Layer 1 relational Blockchain built on PostgreSQL, stands out with its structured data processing capabilities and developer-friendly environment. Leveraging its relational database foundation, Chromia has begun to explore the deep integration of Blockchain and AI technology.

A significant recent development is the launch of "Chromia Extension," which integrates PgVector, an open-source vector similarity search tool widely used within PostgreSQL databases. PgVector supports efficient querying of similar texts or images, providing clear practicality for AI-driven applications.

By integrating PgVector, Chromia introduces vector search capabilities to Web3, aligning its infrastructure with the proven standards of traditional tech stacks. This integration plays a key role in the Mimir mainnet upgrade in March 2025 and is seen as a foundational step towards seamless interoperability between AI and Blockchain.

3.1 Integrated Environment: Complete Fusion of Blockchain and AI

The biggest challenge for developers attempting to combine Blockchain and AI is complexity. Creating AI applications on existing blockchains requires connecting multiple external systems, which is a cumbersome process. For example, developers need to store data on-chain, run AI models on external servers, and build independent vector databases.

This fragmented structure leads to inefficient operations. User queries are processed off-chain, requiring continuous migration of data between on-chain and off-chain environments. This not only increases development time and infrastructure costs but also creates serious security risks, as data transmission between systems increases the risk of hacker attacks and reduces overall transparency.

Chromia provides a fundamental solution by directly integrating vector databases into the Blockchain. On Chromia, all processing is done on-chain: user queries are converted into vectors, similar data is searched directly on-chain, and results are returned, achieving end-to-end processing in a single environment.

This integrated approach greatly simplifies the development process. There is no need for external services and complex connection code, reducing development time and costs. Additionally, all data and processing are recorded on-chain, ensuring complete transparency. This marks the beginning of the complete integration of Blockchain and AI.

3.2 Cost Efficiency: Outstanding price competitiveness compared to existing services.

There is a common perception that on-chain services are "inconvenient and expensive". Especially in traditional Blockchain models, the structural flaw of generating fuel costs for each transaction and the surge in on-chain costs during congestion is significant. The unpredictability of costs has become a major barrier for enterprises adopting Blockchain solutions.

Chromia addresses this pain point through an efficient architecture and a differentiated business model. Unlike the fuel fee model of traditional blockchains, Chromia introduces a Server Computing Unit (SCU) leasing system, similar to cloud service pricing structures. This instantiation model aligns with familiar cloud service pricing, eliminating the common cost fluctuations of blockchain networks.

Specifically, users can lease SCUs on a weekly basis using Chromia's native token. Each SCU provides 16GB of baseline storage, with costs scaling linearly with usage. SCUs can be elastically adjusted according to demand, enabling flexible and efficient resource allocation. This model incorporates predictable usage pricing while maintaining network decentralization, significantly enhancing cost transparency and efficiency.

Chromia's vector database further strengthens its cost advantage. According to internal testing, the monthly operating cost of this database is $727 (based on 2 SCUs and 50GB of storage), which is 57% lower than similar Web2 vector database solutions.

This price competitiveness stems from multiple structural efficiencies. Chromia benefits from the technical optimization of adapting PgVector to an on-chain environment, but the greater impact comes from its decentralized resource supply model. Traditional services impose high service premiums on cloud infrastructure, while Chromia directly provides computing power and storage through node operators, reducing intermediaries and associated costs.

The distributed architecture also enhances service reliability. The parallel operation of multiple nodes naturally endows the network with high availability, even in the event of individual node failures. Therefore, the typical high-cost high-availability infrastructure and large support team requirements in the Web2 SaaS model are significantly reduced, lowering operational costs while enhancing system resilience.

4. The Beginning of the Fusion of Blockchain and AI

Despite being launched only a month ago, the Chromia vector database has already shown early traction, with several innovative use cases in development. To accelerate adoption, Chromia actively supports builders by funding the costs associated with using the vector database.

These grants lower the barrier to experimentation, allowing developers to explore new ideas with reduced risk. Potential applications include AI-integrated DeFi services, transparent content recommendation systems, user-owned data sharing platforms, and community-driven knowledge management tools.

With the growth of diversified use cases, more data is continuously generated and stored on Chromia, laying the foundation for the "AI flywheel". Text, images, and transaction data from blockchain applications are stored in structured vector format in the Chromia database, forming a rich AI trainable dataset.

These accumulated data become the core learning materials for AI, driving continuous performance improvement. For example, AI that learns from the massive user transaction patterns can provide more accurate and customized financial advice. These advanced AI applications attract more users by enhancing user experience, and user growth will in turn generate a richer data accumulation, forming a closed loop of sustainable ecological development.

5. Chromia's Roadmap

After the launch of the Mimir mainnet, Chromia will focus on three key areas:

1. Enhance the EVM indexing of mainstream blockchains;
2. Expand AI inference capabilities to support a wider range of models and use cases;
3. Expand the developer ecosystem through more user-friendly tools and infrastructure.

5.1 EVM Index Innovation

Chromia has launched an innovative indexing solution centered around developers, aimed at fundamentally simplifying on-chain data queries. The goal is clear: to significantly enhance query efficiency and flexibility, making Blockchain data more accessible.

This method represents a significant shift in the way Ethereum NFT transactions are tracked. Chromia dynamically learns data patterns and structures, replacing rigid predefined query structures, thereby identifying the most efficient information retrieval paths. Game developers can instantly analyze on-chain item transaction histories, and DeFi projects can quickly trace complex transaction flows.

5.2 AI reasoning capability expansion

The project has successfully launched its first AI inference extension on the test net, focusing on supporting open-source AI models. It is worth noting that the introduction of the Python client has significantly reduced the difficulty of integrating machine learning models in the Chromia environment.

This development goes beyond technical optimization and reflects a strategic alignment with the fast-paced innovation of AI models. By supporting the direct operation of increasingly diverse and powerful AI models on vendor nodes, Chromia aims to break through the boundaries of distributed AI learning and reasoning.

5.3 Developer Ecosystem Expansion Strategy

Chromia is actively building partnerships to unlock the full potential of vector database technology, with a focus on AI-driven application development. These efforts aim to enhance network utility and demand.

The company aims at high-impact areas such as AI research agency, decentralized recommendation systems, context-aware text search, and semantic similarity search. This plan goes beyond technical support to create a platform for developers to build applications that deliver real user value. The enhanced data indexing and AI reasoning capabilities are expected to become the core engine for the development of these applications.

6. Chromia's Vision and Market Challenges

Chromia's on-chain vector database makes it a leading competitor in the blockchain-AI integration space. Its innovative approach has not been realized in other ecosystems, highlighting a clear technological advantage.

The platform's cloud-based SCU leasing model introduces an enticing paradigm shift for developers accustomed to the fuel fee system. This predictable and optimized cost structure is particularly suitable for large-scale AI applications, constituting a key differentiating factor. Notably, the usage cost is approximately 57% lower than Web2 vector database services, significantly enhancing Chromia's market competitiveness.

Nevertheless, Chromia faces key challenges, particularly in market awareness and ecosystem growth. It is crucial to communicate its native programming language and on-chain AI integration, among other complex innovations, to developers and enterprises. Maintaining a leading position requires continuous technological development and ecosystem expansion, especially as other blockchain platforms begin to target similar use cases.

Long-term success depends on validating actual use cases and ensuring token economics.