I. Outlook

1. Macro-level Summary and Future Predictions

Last Week's Macro Summary (2026/7/6 – 2026/7/12):

Last week, the main themes in European and American macro markets revolved around the Federal Reserve's policy expectations and the pace of Europe's economic recovery. In the US, the June FOMC meeting minutes showed that the Fed still believes inflation is above the 2% target. Despite keeping interest rates unchanged, most officials still lean towards further tightening policies within the year. The market continues to focus on the impact of inflation and employment data on the subsequent policy path. Affected by the weakening of previous non-farm payroll data and falling energy prices, market expectations for an immediate rate hike in July have cooled, and risk assets have performed relatively strongly. In Europe, data such as German industrial orders and industrial production indicate that the manufacturing sector remains weak, but overall inflationary pressure in the Eurozone continues to ease. The European Central Bank maintains a cautious wait-and-see attitude, and the market expects policy to remain stable in the short term.

Next Week's Forecast (2026/7/13 – 2026/7/19):

Next week, the US will release June CPI, PPI, retail sales, the Federal Reserve Beige Book, and Fed Chairman Kevin Warsh's first congressional testimony. These will become the most important pricing factors for global markets. If CPI continues to decline, it will further strengthen market expectations for rate cuts or delayed rate hikes within the year, benefiting US stocks and global risk assets. If inflation rebounds more than expected, the US dollar and US Treasury yields may strengthen again, putting pressure on risk assets. In Europe, the market will focus on Eurozone industrial production and inflation data. If economic data continues to be weak while inflation continues to fall, it will further consolidate the market's judgment that the European Central Bank will keep interest rates unchanged or even release easing expectations.

2. Cryptocurrency Industry Market Changes and Warnings

Last Week's Summary (2026/7/6 – 2026/7/12): The crypto market showed a volatile recovery trend last week. On July 6, affected by Strategy's (formerly MicroStrategy) disclosure of selling approximately 3,588 BTC (about $216 million), Bitcoin briefly fell to around $61,300. Subsequently, as spot ETF funds flowed back in and buying power recovered, BTC rebounded to $63,163 on July 7, briefly fell back to $62,247 on July 8, closed at $63,795 on July 11, and fluctuated around $63,600 on July 12. ETH performed relatively steadily, maintaining a range of $1,760–$1,800 during the week, recently around $1,790. Market hotspots remain focused on AI, RWA, stablecoin infrastructure, and institutional-grade DeFi yield protocols. Overall risk appetite improved compared to the previous week, but trading volume remained cautious.

Next Week's Forecast (2026/7/13 – 2026/7/19): The market is expected to continue being primarily driven by macroeconomic data, ETF fund flows, and institutional capital movements. If BTC can firmly hold above $64,000, it may further test the resistance zone of $65,000–$66,000. If it breaks below $62,000 again, it could retest the support area of $60,000–$61,000. ETH is expected to fluctuate in the $1,750–$1,850 range, with its trend still driven by BTC. In the short term, sectors like RWA, stablecoins, AI Agents, on-chain Yield, and institutional infrastructure are still expected to maintain high attention, but one must be wary of market volatility caused by macro events and large institutional capital flows.

3. Industry and Sector Hotspots

From July 6 to July 12, 2026, the crypto industry hotspots mainly revolved around "institutional-grade infrastructure, AI, RWA, and stablecoin yield." In terms of financing, Elliptic completed a $125 million strategic financing round, further promoting on-chain compliance and blockchain analysis capabilities. KOR Protocol completed a $7.5 million Series A financing round, focusing on digital content/IP on-chain infrastructure. Mercado Bitcoin received a $20 million strategic investment, continuing to advance its RWA and institutional asset tokenization布局.

Technologically, institutional-grade yield infrastructure, RWA yield assets, cross-chain liquidity, and AI-driven financial automation remain key industry directions. More and more projects are focusing on connecting traditional financial institution funds with on-chain yield markets through APIs, modular architectures, and automated asset allocation, reflecting the crypto industry's continuous trend towards institutionalization, asset tokenization, and the convergence of AI and DeFi.

II. Market Hotspots and Potential Projects of the Week

1. Overview of Potential Projects

1.1. Detailed Look at Jia: An On-Chain Credit Network Connecting Global Capital with Real-World Yield in Emerging Markets, Raising $7.3M Led by Coinbase and TCG, with Participation from Strobe, Hashed Emergent, and SAISON

Introduction

Jia is a decentralized lending protocol and fintech platform designed to connect capital with micro and small enterprises in emerging markets that have real yield potential.

By providing loans to micro and small businesses, Jia aims to bridge the gap in financial service accessibility, offering fairer and more convenient short-term financing channels to groups long ignored by the traditional financial system.

On its platform, Jia incentivizes ecosystem-beneficial behaviors, partners with high-quality data providers, and utilizes a reward token mechanism to provide investors with a consistent and stable source of yield, while helping businesses in underdeveloped markets obtain the capital they need to grow.

Brief Protocol Mechanism

The Jia protocol is mainly composed of four core participants, collectively building its on-chain credit system for emerging markets.

1. Borrowers

Borrowers are primarily micro-enterprises and SMEs (MSMEs) from emerging markets.

These businesses obtain financing through Jia's lending pools to operate and grow.

Borrowers can be referred to Jia through Partners or apply for loans directly. To obtain better loan terms, borrowers can also provide collateral.

In terms of user experience, borrowers operate through a simple mobile application, with the underlying blockchain technology being transparent to users, who don't need experience using crypto assets.

2. Lenders

Lenders are investors who provide capital to Jia's lending pools.

After depositing funds into the protocol, they earn interest income from borrower repayments, thereby sharing in the Real Yield generated by the real economy of emerging markets.

3. Sponsors

Sponsors hold on-chain assets and use these assets as loan collateral.

For borrowers with insufficient credit history or higher risk who would otherwise struggle to pass risk control reviews, Sponsors provide additional credit support to help them obtain financing opportunities.

Essentially, they act as a credit enhancement role within the protocol.

4. Partners

Partners are typically business platforms or ecosystem partners serving the borrowing enterprises.

They are responsible for:

• Recommending high-quality borrowers to Jia
• Providing operational and business data
• Assisting with loan risk control and credit assessment

This data is used in the protocol's loan underwriting process, helping to improve risk control accuracy.

Lending Mechanics

Loan Terms

Jia primarily addresses the most pressing financing needs of small businesses in emerging markets: short-term working capital loans.

Standard loan products typically have the following characteristics:

• Loan Amount: $100 – $5,000
• Loan Term: 30 – 90 days
• Monthly Interest Rate: 2% – 7%

Specific loan conditions are customized based on the borrower's credit status, business situation, and financing needs, and are continuously optimized as borrowing history accumulates.

While this interest rate level may seem high to investors in European and American markets, it is a relatively common commercial loan interest rate level in the emerging markets Jia serves. The shorter loan cycles also help improve capital turnover efficiency, bringing continuous and stable returns to investors.

During the loan approval process, Jia evaluates data from multiple dimensions, mainly including:

Partner Data

Partners are often the platforms that borrowing enterprises rely on for daily operations.

They can provide:

• Sales data
• Inventory data
• Revenue data
• Operational behavior data

This data helps Jia better understand the business's operational status.

Borrower Application

Borrowers need to submit a loan application and disclose:

• Income situation
• Expense situation
• Use of funds
• Business information

This serves as an important basis for credit review.

Third-party Data

Jia also integrates external financial data sources, such as:

• Local credit bureaus
• Bank data
• Financial service platforms

Further supplementing the borrower's credit information.

Underwriting (Smart Risk Control Review)

Unlike most DeFi lending protocols that rely on over-collateralization, Jia's core innovation lies in:

Supporting unsecured or under-collateralized credit loans (Unsecured Lending).

To this end, Jia utilizes high-quality financial data from partners, borrowers, and third-party agencies to establish a credit assessment model based on Machine Learning.

The system comprehensively analyzes the enterprise's:

• Operational capability
• Income stability
• Historical repayment performance
• Cash flow situation
• Credit history

This allows it to assess loan risk and determine credit limits and loan conditions.

User Flow

JIA Token and Community Incentive Mechanism

Jia not only aims to provide financing for small businesses but also hopes to make borrowers long-term participants and beneficiaries of the entire ecosystem.

Taking Alice as an example, under the traditional financial system, due to limited financing channels, she often could only obtain high-cost loans, resulting in a one-way lending relationship with the lending institution. Even if her business continues to grow, she cannot share in the returns generated by the financial platform's development.

In the Jia system, when Alice establishes a long-term, good borrowing relationship with the platform, she can earn JIA token rewards by participating in the ecosystem. As she accumulates JIA, her identity transforms from being just a borrower into a co-builder and stakeholder of the protocol.

By holding JIA, she can:

• Participate in protocol governance
• Vote on the future development direction of the platform
• Share in the value generated by the protocol's long-term growth
• Align her interests with the entire ecosystem

Through this mechanism, Jia hopes to upgrade the original simple "lending relationship" into a "relationship of mutual growth."

Tron's Take

Jia's advantage lies in its combination of DeFi capital with the real economic needs of emerging markets, specifically serving small businesses long overlooked by traditional finance. By utilizing partner data, third-party financial data, and machine learning risk control models to provide unsecured or under-collateralized loans, it generates yields derived from real business activities (Real Yield). Simultaneously, the JIA token incentive mechanism allows borrowers, investors, and ecosystem participants to share in the platform's growth value, combining inclusive finance with on-chain financial innovation.

However, its disadvantage is that the business is essentially credit lending, exposing it to risks such as borrower default, data authenticity, risk model failure, and macroeconomic volatility in emerging markets. It also requires continuous reliance on local partners for high-quality operational data, making operational complexity and compliance requirements much higher than traditional over-collateralized DeFi protocols. Future scaling will also face challenges related to regional regulation and asset quality management.

2. Key Project Detail for the Week

2.1. Detailed Look at Manadia: Building a Verifiable Collaboration Network Driven by AI and Privacy Computing, Led by AurumX (Financing Amount Unknown)

Introduction

Manadia is a Web3 infrastructure platform deeply integrating AI Collaboration and Privacy Computing, focused on achieving:

• Verifiable Data Settlement
• Privacy-Enhanced Value Transfer
• Efficient Cross-System Coordination

Its core goal is to break down trust barriers between on-chain and off-chain systems through standardized technical protocols and tooling, building reliable, secure, and verifiable collaboration environments for high-value scenarios like finance and asset digitization, without relying on any single trusted third party.

Core System Architecture Analysis

VERITAS – Real-World Data Injection and Adjudication Protocol

VERITAS is the core protocol within manadia for processing external world input information, designed to generate on-chain signals that are resistant to manipulation and open to challenge and verification. It combines multi-source data aggregation, economic penalty mechanisms, and a hybrid verification process, moving beyond the limitations of traditional oracles that simply "provide price data."

For high-frequency price data injection, VERITAS employs a Weighted Median-based data aggregation algorithm: the system collects signed data from multiple nodes (pre-selected validators) and generates a consensus price through deviation detection (calculating Z-scores, filtering outliers with thresholds greater than 3).

The economic incentive mechanism uses a Staking–Slashing model: nodes must lock $MA tokens as collateral. When the data they provide deviates by more than 5%, the slashing mechanism is automatically triggered, with the slashing ratio calculated based on historical reputation and an exponential decay model.

Compared to Chainlink's simple voting mechanism, this approach is more robust and can resist flash loan attacks through time-lock delayed confirmation mechanisms.

For example:

In a DeFi liquidation scenario, VERITAS can push ETH/USD prices every 5 seconds, supporting sub-millisecond derivative pricing.

For complex event verification, VERITAS introduces a hybrid model combining AI and human game theory.

First, an integrated Large Language Model (e.g., Groq series) parses news APIs or off-chain signals, automatically generating event proposals and outputting structured assertions.

Subsequently, the system opens a fixed challenge window (e.g., 24 hours). During this period, any token holder can submit a counter-evidence and initiate a challenge, simultaneously staking an equivalent amount of $MA tokens to participate in the economic game