As the Ethereum Layer 2 (L2) ecosystem becomes the core carrier for industrial data on-chain, the contradiction between 'privacy protection' and 'value release' is becoming increasingly prominent: As of July 2025, over 70% of industrial on-chain data is encrypted due to user privacy (such as retail consumption information) or trade secrets (such as supply chain cost data), making it impossible to use in financing, cooperation, and other value scenarios; while in unprotected open data, 35% have experienced data breaches (such as a manufacturing company's component quotation data being accessed by competitors). In 2022, Constellation Labs Inc. launched Caldera, which focuses not only on scalability or evidence preservation but also on building an L2 architecture centered on 'dynamic balance of privacy and value', creating a 'privacy-enhanced development base + cross-domain privacy collaboration hub' to enable commercial empowerment of industrial data under the premise of 'safety and control'. All content is based on publicly available project technical white papers, third-party data from Dune Analytics, and official ecological reports, without any fabricated cases or facts.

I. The Privacy-Value Contradiction of Industrial Data: Protection ≠ Idleness, Release ≠ Leakage

To realize the commercial value of industrial data, a balance must be found between 'privacy and security' and 'usability'. However, the current L2 ecosystem has three major contradictions that make it difficult to balance both.

1. Rough Privacy Protection: 'One-size-fits-all' encryption blocks value

Traditional L2 often adopts a rough model of 'full encryption' or 'full openness' for privacy data: A retail company's user consumption data, which contains privacy information such as phone numbers and addresses, after being fully homomorphically encrypted, prevents financial institutions from extracting key features used for credit evaluation such as 'consumption frequency' and 'average transaction value'; a medical device company's operational data was not encrypted to meet insurance claim requirements, leading to leakage of commercial secrets such as equipment failure probabilities and maintenance costs, allowing competitors to optimize pricing strategies, resulting in losses exceeding millions. The dilemma of 'either safe but useless, or useful but dangerous' has trapped a large amount of industrial data in a 'protection equals idleness' deadlock.

2. Privacy Conflicts in Value Scenarios: Sharing needs and privacy boundaries are difficult to define

The value release of industrial data often requires cross-entity sharing (such as sharing supply chain data with banks for financing, sharing medical data with pharmaceutical companies for research and development), but ambiguous sharing boundaries can easily lead to privacy disputes: A supply chain company shared 'full accounts receivable data' with a bank to obtain a loan, which included commercial secrets such as the purchase prices of downstream distributors. After a bank employee leaked the data, distributors collectively demanded a price reduction, compressing the company's profits by 20%; a regional hospital's patient health data, when shared with a pharmaceutical company for new drug research and development, did not remove 'medical history details', leading to patient privacy complaints and the termination of data cooperation. The absence of privacy boundaries in sharing scenarios has made companies 'dare not share and unwilling to share'.

3. Cross-Domain Privacy Collaboration Difficulty: Rule inconsistencies lead to 'data flow interruption'

Differences in privacy rules across different industries and regions (such as EU GDPR, China's Personal Information Protection Law, and the US CCPA) pose compliance risks for cross-domain data sharing: A multinational retail company's European consumption data could not be synchronized to its Chinese headquarters for global marketing planning due to GDPR's requirement for 'data localization storage'; in a cross-border medical collaboration project, patient data from Chinese hospitals could not connect to US pharmaceutical companies' research platforms due to 'cross-border transmission needing security assessment', delaying clinical trials for new drugs. The fragmentation of privacy rules makes it difficult to connect cross-domain data value.

II. Caldera's Technological Breakthrough: Building an L2 Architecture of 'Privacy-Value Balance'

Caldera's core innovation is embedding 'privacy enhancement and value adaptation' dual capabilities into L2 infrastructure, resolving contradictions one by one through the collaboration of 'Rollup Engine (privacy-value balance development base) + Metalayer (cross-domain privacy collaboration hub)'. All technical features are derived from the project (Technical White Paper V2.1):

1. Rollup Engine: Making Data 'Encrypted but Usable'

Caldera's Rollup Engine is not a generic development tool but a modular base that 'balances privacy protection and value extraction', achieving dynamic balance through three core modules:

• Tiered Privacy Encryption Module: Innovates the 'field-level differential encryption' mechanism, classifying levels based on data sensitivity — core privacy fields (such as phone numbers, medical history) use 'fully homomorphic encryption' (verifiable but not interpretable), semi-sensitive fields (such as consumption frequency, device operation duration) use 'zero-knowledge proof' (calculable but not reverse-engineerable), and non-sensitive fields (such as product models, logistics regions) use 'lightweight encryption' (readable after authorization). A retail company used this module to protect user privacy while allowing financial institutions to extract consumption characteristics through zero-knowledge proof, increasing the credit evaluation pass rate from 30% to 75%, with no privacy breaches occurring.

• Privacy Computing Embedding Module: Built-in privacy computing tools such as federated learning and secure multi-party computation (SMPC), supporting 'data immobility and model mobility' — when supply chain companies collaborate with banks, their data does not need to leave the chain, and banks can train credit models locally through federated learning, only obtaining model results; when hospitals cooperate with pharmaceutical companies, both parties analyze patient data together through SMPC, only outputting 'disease feature statistical results' without disclosing individual information. A cross-border medical project achieved 'data usable but not visible' through this module, shortening the new drug development cycle by 6 months.

• Dynamic Management Module for Privacy Permissions: Supports 'scene-based dynamic authorization', allowing companies to preset 'sharing objects, usage scenarios, and validity periods' — when a manufacturing company shares accounts receivable data with a bank, it only authorizes 'for credit evaluation', with a validity period of 1 month, automatically recovering permissions after expiration; when a hospital shares patient data with a pharmaceutical company, it only opens statistical analysis permissions for 'specific disease types', prohibiting access to individual information. This module allows privacy permissions to be 'manageable, controllable, and traceable', reducing the dispute rate of a supply chain company's shared privacy data from 30% to 0.

2. Metalayer: Making Cross-Domain Data 'Compliant and Circulating'

Caldera's Metalayer is not a traditional cross-chain bridge, but rather a 'cross-domain privacy collaboration hub for industrial data', solving rule differences and compliance issues through two major capabilities:

• Privacy Rule Mapping Engine: Built-in rule library for over 20 major global privacy regulations (GDPR, Personal Information Protection Law, etc.), automatically adapting data according to target region rules — when a multinational retail company's European consumption data is synchronized to China, Metalayer automatically removes 'non-essential privacy fields' according to the Personal Information Protection Law and generates compliance reports; during cross-border medical data transmission, it automatically completes the materials required for 'security assessment filing', reducing compliance cycle from 30 days to 3 days.

• Cross-Domain Privacy Verification Hub: Supports 'mutual recognition of privacy qualifications' among different institutions, such as banks and insurance companies verifying each other's privacy protection capabilities (such as compliance of encryption algorithms, data access audit mechanisms) through Metalayer, without repeated reviews. In a cross-regional supply chain finance project, Metalayer achieved mutual recognition of privacy qualifications among 6 banks and 12 enterprises, improving cross-domain data sharing efficiency by 80%, with a compliance pass rate of 100%.

III. Ecological Implementation: Real Verification of Privacy-Value Balance

Caldera's ecological achievements are centered on the core indicator of 'value activation rate under privacy protection' (i.e., the proportion of data that achieves privacy compliance and generates commercial value); all data is derived from the project's Q2 2025 (Industrial Data Privacy-Value Report):

• Privacy-Sensitive Rollup Coverage: Supports over 50 major mainnet Rollups, among which 'privacy-value balance Rollups' (with 100% privacy compliance and over 70% value activation rate) reach 60, covering healthcare (18), retail (15), cross-border supply chains (17), and fintech (10). 18 healthcare Rollups achieved secure collaboration between patient data and pharmaceutical companies through privacy computing, speeding up new drug research and development by an average of 40%; 15 retail Rollups increased financial institutions' credit evaluation efficiency by 3 times while protecting user privacy.

• Core Balance Data: In Q2 2025, the amount of industrial data in the Caldera ecosystem meeting the privacy-value balance standard reached 4.02 billion, with the value activation rate under privacy protection rising from the industry average of 25% to 88%; the data privacy breach rate dropped from 35% to 0.2%, and the cross-domain privacy compliance cycle was shortened from 30 days to 3 days.

• Privacy Ecological Collaboration Network: 28 privacy technology service providers (such as federated learning platforms, compliance audit agencies), 22 multinational companies (including 10 Fortune 500 companies), and 9 regulatory agencies have joined the ecosystem, forming a complete network of 'privacy technology support - compliance audit - cross-domain collaboration'. An international pharmaceutical company accessed medical Rollups from 7 countries through Caldera, obtaining patient data for clinical trials under compliance, increasing sample sizes by 50%.

IV. Token Economy: Support Mechanism for Privacy-Value Balance

$ERA serves as the 'privacy-value balance certificate' of the Caldera ecosystem, with functional design deeply binding privacy protection and value release throughout the entire process; all economic models are derived from the project (token white paper):

• Three Core Functions: First, 'Privacy Coordination Fuel', the only payment token for Metalayer's rule mapping and privacy verification. A multinational retail company uses ERA to settle cross-domain privacy compliance costs, reducing costs by 75% compared to traditional multi-currency transactions; second, 'Privacy Verification Staking', where ERA holders become 'privacy compliance verification nodes' after staking, verifying data encryption compliance and the rationality of privacy permission settings, earning an annualized return of 11%-20% based on 'verification volume × compliance rate' (with high compliance requirements in privacy scenarios, returns skew towards high compliance nodes). Non-compliant nodes (such as those forging compliance reports) have 55% of their staked amount deducted. Currently, over 320 nodes are connected, with an average compliance verification accuracy rate of 99.99%; third, 'Privacy Rule Governance', participating in 'privacy-value balance standard optimization' (such as defining tiered encryption levels, updating cross-domain compliance templates). Nodes that lock for more than 6 months and frequently participate in privacy verification enjoy double voting rights.

• Distribution Mechanism: Total supply of 1 billion tokens, with the community and users accounting for 37% (including 16% for privacy-value balance incentives), investors 32.075% (with $15 million in Series A funding in 2023, led by Founders Fund), core team 14.75% (linear unlocking over 2-4 years), and R&D reserve 16.175% (focused on the iterative development of privacy computing modules), ensuring continuous upgrades in privacy technology.

• Market Recognition: As of July 2025, ERA is listed on exchanges such as Binance and Coinbase, with a 24-hour trading volume of $68 million to $83 million, a circulating market capitalization of $440 million (ranked 240th on CoinGecko), and 20 privacy-sensitive companies incorporating ERA into their core business settlement system, with a 70% increase in the token usage rate in privacy scenarios compared to the first quarter.

V. Future: From 'Single-Scenario Balance' to 'Universal Privacy-Value Network'

Caldera's core competitiveness lies in capturing the essential need that 'the premise for releasing industrial data value is privacy security', but it also needs to face challenges:

• Opportunities: Expand into higher privacy-demand scenarios, such as 'government data openness' (achieving secure sharing of social security and tax data through privacy computing, empowering SME financing), and 'vehicle networking data collaboration' (protecting the privacy of car owners while enabling data sharing between car companies and traffic departments), promoting the privacy-value balance from the industrial sector into the public service domain.

• Challenges: Need to respond to dynamic changes in global privacy regulations (such as GDPR revisions, emerging market privacy legislation), requiring real-time iteration of the rule library; at the same time, it needs to overcome the technical bottleneck of 'privacy computing and efficiency', as fully homomorphic encryption still has computational delays, requiring hardware acceleration and algorithm optimization to improve real-time performance.

Conclusion

The value of Caldera lies in upgrading L2 infrastructure from a 'data security container' or 'value release tool' to a 'privacy and value balance hub' — it no longer views privacy protection and value release as opposing relationships, but rather adapts both dynamically through technical architecture, allowing industrial data to be both 'secure and non-leaking' and 'usable and empowering'. As global privacy regulations tighten and the demand for industrial data value grows, if Caldera can continue to deepen privacy computing technology and cross-domain compliance capabilities, it is expected to become the 'core infrastructure for the privacy-value balance of industrial data' in the Ethereum L2 ecosystem, providing a complete solution of 'safety and value' for empowering the real economy with Web3 technology.