Tiger Research: Realism is the only answer during the cryptocurrency downturn.

  • In a bearish cryptocurrency market, practical projects survive.
  • Key evaluation criteria: address real market problems, offer practical solutions, team execution capability.
  • Example projects:
    • Hyperliquid: Solves transaction friction with decentralized perpetual contracts.
    • Canton Network: Provides privacy-compliant infrastructure for institutional finance.
    • Kite AI: Builds payment infrastructure for the future AI economy.
  • Focus on real-world feasibility when assessing projects.
Summary

This report, written by Tiger Research , discusses the ongoing long-term decline in the cryptocurrency market. In this environment, projects that demonstrate a pragmatic and realistic vision are the ones that will survive.

Key points

  • Projects that solve real, specific problems can remain resilient even during market downturns.
  • Hyperliquid, Canton, and Kite target different problem domains, but they share a common characteristic: providing practical and realistic solutions rather than abstract narratives.
  • To assess this reality, the analysis should focus on three factors: the problem the project aims to solve, the structure of the solution, and the team's ability to execute it in practice.

1. Survival conditions in a bear market: Is it effective in practice?

Bitcoin has fallen below $70,000. Of the top 100 cryptocurrencies by market capitalization, only seven remain above their 200-day moving average. In contrast, 53 of the Nasdaq 100 index components are still trading above that threshold.

Market conditions are beyond our control. Nevertheless, some crypto assets manage to survive even the worst environments.

Their resilience cannot be simply attributed to market manipulation or accidental rebounds. A closer look at their trajectory reveals different explanations.

These projects no longer rely solely on vague visions or technological complexity. Instead, they share a common characteristic: addressing core market problems with solutions rooted in real-world realities. Their approach typically follows three directions:

  1. Do they solve the problems currently facing the market?

  2. Are they ready for near-term practical application?

  3. Are they building the infrastructure that the industry has relied on for a long time?

Ultimately, the ability to solve real-world problems in practice remains the strongest fundamental advantage.

2. Three directions of market selection

Projects that were able to answer the above questions survived. Their approach was to: 1) clearly identify the market problem; and 2) propose practical solutions that were appropriate for the specific timeframe.

2.1. Hyperliquid: Resolving Friction in Real-Time Transactions

Centralized exchanges are traditionally seen as responsible intermediaries. However, in practice, they often fail to align with investor interests when problems arise. Decentralized exchanges emerged as an alternative, but their poor user experience and performance have deterred many investors.

Against this backdrop, Hyperliquid introduced the concept of a perpetual contract decentralized exchange (perp DEX). Through the HLP mechanism, it brings features valued by investors in centralized exchanges—such as high leverage, fast execution, and stable liquidity—to the on-chain environment.

Early usage was partly driven by demand for the $HYPE token airdrop. However, continued engagement after the airdrop reflects user satisfaction with the platform's performance.

Ultimately, Hyperliquid's resilience stems from addressing a persistent real-world problem: dissatisfaction with centralized exchanges.

2.2. Canton Network: Preparing for the Era of Institutional Finance

Canton proposes a solution geared towards the near future. With the continued rise in interest in real-world assets (RWA), institutions are beginning to view blockchain as financial infrastructure rather than a public network. In this context, what institutions need is not complete data transparency, but rather selective privacy models that support regulatory compliance and confidentiality.

Canton Network was created to address this need. Through DAML, Canton is able to provide configurable data disclosure for each participant.

This allows institutions to share information only where necessary while maintaining transaction confidentiality. Canton does not impose a provider-driven design, but rather builds infrastructure that meets the needs of institutions.

Another key factor is that Canton has focused on real-world deployments to expand its ecosystem from the outset, and has been supported by early partnerships with financial institutions.

Most notably, its partnership with DTCC establishes a pathway for assets managed by the traditional financial system to expand into a Canton-based environment. DTCC processes approximately $3.7 quadrillion in transactions annually, highlighting the practical viability of the Canton Network approach.

Ultimately, Canton Network offers a structured solution designed to meet the requirements of three institutions simultaneously: privacy protection, regulatory compliance, and integration with existing financial systems.

2.3. Kite AI: Building the AI ​​Economy Yet to Come

Unlike the previous two examples, Kite AI currently has limited practical applications. However, from the future perspective of AI agents operating as economic agents, its structural logic remains compelling.

In the Web2 and Web3 domains, there is a broad consensus on the future of agent-driven computing. Few question the use of AI agents to handle tasks such as booking hotels or purchasing daily necessities on behalf of users.

However, such a future requires infrastructure that allows AI agents to independently initiate and execute payments. Existing transaction systems are designed around transfers between people and efficiency among human participants.

Therefore, new mechanisms, including identity verification and automated payment frameworks, are needed for AI agents to operate as autonomous economic entities.

Kite AI is building payment infrastructure for this environment. Its core components include a "proxy passport" for authentication and x402 protocol functionality for enabling automated payments.

Kite AI's vision cannot be deployed on a large scale at present, simply because the future it envisions has not yet been realized.

Nevertheless, the project's viability stems from a broader premise: that the underlying technology it is developing will be necessary when this widely anticipated future arrives. This alignment with a widely accepted development trajectory lends the project structural credibility, despite its current limited use.

3. Three key issues in assessing practical feasibility

Although these three projects have different timelines, they share a common feature: real-world feasibility.

Evaluations of the same project often differ. Some believe it solves a real problem, while others think it's been overhyped. To bridge this interpretive gap, at least three core questions must be asked:

  1. What problem does it solve? Does the problem the project addresses actually exist and have market demand?

  2. How does it solve this problem? Is the proposed solution structurally sound and feasible?

  3. Who is executing it? Does the team have the capability and resources to turn the vision into reality?

Since most projects promote an optimistic future narrative, answering these questions correctly requires time and effort. Filtering out misleading or incomplete information is no easy task. Projects that cannot confidently answer these three questions may experience short-term price increases, but they are likely to disappear when the next downturn arrives.

The current state of the cryptocurrency market is clearly unfavorable. But this doesn't mean it's all over. New experiments will continue, and the task is to assess what these efforts truly represent.

Realism is the most important thing now.

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Author: Tiger Research

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