Stablehunter helps users understand, compare, and allocate on-chain stable assets by translating complex DeFi yields into a risk-structured decision system.Not higher yield hunting — but clearer risk boundaries.
Stablecoin Management: A Paradigm Shift from "Crypto Tool" to "Global Dollar Liquidity Layer"
Stablecoins are evolving beyond niche crypto tools to become a foundational layer for global dollar liquidity. Our market analysis breaks down this significant shift into three key segments:
Yield-bearing Stablecoins & Tokenized Real World Assets (RWA)
2030 Scale: $400 Billion - $600 Billion
Serviceable Obtainable Market (SOM)
Aggregator Monetization Market
Target: $24 Billion+ Asset Under Management (AUM)
These projections are primarily sourced from Citigroup's "Stablecoins 2030" Citi GPS report and Dataintelo's 2025 market insights.
The Gap Today
Asset allocation needs a risk framework
Traditional finance
• Shared risk tiers (e.g. low → high risk)
• Clear asset roles in a portfolio
• Allocation decisions come before product selection
On-chain today
• Yield-first discussions
•Familiar labels replace risk classification
•Products compared without a common baseline
What’s missing is not assets or innovation —but a shared risk framework that allocation decisions can anchor to.Without it, allocation becomes intuitive rather than structured.
A Risk Framework for Asset Allocation
Not all risks are the same. In asset allocation, different risks answer different questions and fail in different ways. Treating them as one obscures risk rather than clarifying it.
A practical risk framework separates allocation risk into layers:
1
2
3
4
5
1
Allocation
2
Behavior
3
Liquidity
4
Structure
5
Survival
This framework does not predict outcomes. It clarifies where different risks belong.
From Framework to Stablehunter.AI
Turning risk understanding into decision intelligence
Understanding risk is necessary, but not sufficient. Most users do not struggle with access to assets. They struggle with interpreting risk, structure, and trade-offs across layers.
Stablehunter ' Role
Stablehunter sits between on-chain assets and allocation decisions. It does not replace judgment. It structures it.
Product Essential
Stablehunter is a decision intelligence layer for Web3 asset allocation.
It helps users
It helps users:
interpret risk across layers
compare assets on a common framework
make allocation decisions with clearer boundaries
Product Roadmap From interpretation to decision intelligence
This roadmap is not a feature timeline. It reflects how allocation decisions are progressively externalized into product capabilities.
Stablehunter 1.0 — Interpretation Layer
1.0 focuses on interpretation.
Structured risk analysis across layers
Transparent breakdown of product structure
Comparable views across assets
Stablehunter 2.0 — Decision Assistance（AI）
2.0 introduces decision assistance.
Personalized risk interpretation
Scenario-based impact evaluation
AI-assisted allocation suggestions
Stablehunter 3.0 — Allocation Infrastructure
3.0 moves toward allocation infrastructure.
Model-driven portfolios
Strategy-level products
Managed exposure across asset types
Each stage builds on the previous one. Skipping layers increases risk, not speed.
Who This Is For
Three groups already experiencing the shift
Stablehunter is not built for beginners.It is built for users whose relationship with risk is already changing.
Group 1｜Native Web3 participants, reallocating risk
Native Web3 participants with repeated drawdowns
Moving away from single-bet speculation
Using stablecoins to access equities, gold, and real-world exposure
Group 2｜Global stablecoin earners, using exchanges as banks
Individuals and teams earning in stablecoins globally
Treat exchanges and wallets as primary financial accounts
Seeking capital preservation and structured yield
Group 3｜Web2 allocators entering Web3 cautiously
Experienced allocators from traditional finance
Exploring Web3 for higher returns with controlled risk
Looking for familiar decision frameworks in a new environment
What these groups share is not return expectations, but a need to understand risk before allocating capital.
Why Now
This shift is not driven by a single cycle. It is the result of multiple structural changes converging at the same time.
Driver 1｜Risk awareness after repeated cycles
After multiple boom-and-bust cycles, participants no longer treat volatility as temporary. Risk is no longer theoretical. It has been experienced.
Stablecoins are no longer just settlement tools. They are becoming units of account, stores of value, and sources of income.
Driver 3｜Traditional allocators reaching the boundary
In traditional finance, risk-adjusted returns have compressed. Allocators are not seeking speculation, but new environments with familiar discipline.
Conclusion
What is missing is not access to assets, but a way to interpret and compare risk across these converging flows. This is why decision intelligence, not execution, becomes the bottleneck.
Business Model
How Stablehunter captures value over time
Stablehunter does not start by selling financial products. It monetizes decision quality first, and gradually participates in value distribution.
1
Product Distribution & Rebates（Mid Stage）
As trust is established, Stablehunter participates in product distribution. Revenue comes from transparent rebates, not preferential ranking or traffic selling
2
Proprietary Strategies & Products（Later Stage）
At later stages, Stablehunter introduces model-driven strategies and proprietary allocation products.This stage follows sufficient scale, data, and trust.
Stablehunter grows by improving decisions, not by encouraging more transactions.
Why us?
Stablehunter is built by a team that has repeatedly worked at the intersection of business execution, complex products, and financial infrastructure.
Founder｜Business, GTM & Industry Insight
Founder with 11 years of continuous entrepreneurship, deep experience in B2B, GTM, and commercialization.Over the past 8 months, gained hands-on understanding of Web3 payments, and developed system-level insight into the industry.
CPO｜Product, Growth & Organizational Discipline
CPO previously served as VP of Product, leading product design, user growth, and agile organization practices.Over 12 years of hands-on product leadership across consumer, social, and 2B financial products.
On-chain & infrastructure execution
The team combines: • on-chain asset product experience across market cycles • engineering leadership from large-scale consumer platforms • senior full-stack execution capability
Lean, deliberate team structure
The team currently consists of 8 members and is intentionally designed to remain lean, scaling thoughtfully within a range of 8–12 people.
This team is built to turn abstract frameworks into working systems — and to do so without rushing ahead of understanding.
Prototype v1.0
Stablehunter v1.0 is not a feature demo. It is a working prototype that turns risk interpretation into a visible process.
v1.0 validates three core assumptions:
Risk can be structured across layers
Assets can be compared beyond yield
Users value clarity before execution
Today, v1.0 is used to:
Test real decision workflows
Refine risk language and presentation
Collect early user feedback
As part of v1.0 validation, Stablehunter currently supports off-market retail access to XAUT. This allows us to observe how users interpret structure, custody, and liquidity risks before making allocation decisions.
v1.0 does not automate decisions or take asset positions. Additional asset formats will be explored only after the framework proves robust.
Designed to support 15–18 months of focused execution
Current stage
Stablehunter has a working prototype today, with v1.0 scheduled to go live in January. This round focuses on validation, not simply completing a product launch.
Validation milestones (during this round)
0–3 months
Real users actively use Stablehunter to inform decisions
3–6 months
Willingness to pay for clarity and risk understanding is validated
6–12 months
Decision framework proves consistent across market conditions
12–18 months
System is ready to evolve into AI-assisted decision layers
Use of Funds资金如何使用
Product & Decision System
~40%
Launch and iterate Stablehunter v1.0; formalize the multi-layer risk framework; build data pipelines and decision logic; prepare AI-assisted decision layers
Team & Core Execution
~35%
Maintain a lean 8–12 person team across product, engineering, research, and operations
Real-world Validation & Asset Access
~15%
Support limited real-asset access (e.g. XAUT); observe user interpretation of structure, custody, and liquidity; stress-test the framework
Governance, Compliance & Operations
~10%
Legal, financial, and compliance foundations; security and infrastructure; operational resilience
Why Stablehunter · Why Now
Why Stablehunter
Decision intelligence, not yield aggregation
A structured risk framework built for real allocation decisionsDesigned for clarity before scale
Why Now
Capital is already on-chain, but decision tools lag behind
Users are shifting from leverage to controllable risk
Decision-making is the current system bottleneck
Investment Highlights
Seed-stage opportunity with clear validation milestones (15–18 months)
Disciplined capital deployment, controlled burn
Long-term optionality across AI, RWA, and asset management infrastructure
Closing Statement
Stablehunter helps users understand where they stand, before deciding where to go.