User Profiling Engine
Vingt.io’s AI Smart Agents analyze markets and understands you. The User Profiling Engine is a foundational component of our intelligence stack that allows each investor to receive personalized portfolio strategies based on their preferences, capital, and behavior.
Whether a user is seeking stablecoin yield, swing trading bluechips, or deploying high-conviction leverage, the engine dynamically matches them to the right risk-adjusted allocation across Vingt.io’s index products, trading strategies, and leverage tokens.
How the User Profiling Engine Works
Each user is classified into a risk tier and associated with a behavioral and capital profile, which drives all AI recommendations and alerts.
Risk Appetite Calibration
Users are segmented into three main categories based on onboarding inputs and in-app behavior:
Low Risk: Seeks capital preservation and stable yields. Avoids leverage and prefers diversified, lower-volatility exposure (e.g., SIT, BSK).
Medium Risk: Accepts volatility for moderate growth. Prefers index + strategic token positions (e.g., BTX, ETX, BNBX).
High Risk: Comfortable with aggressive strategies. Uses leverage products, trades narrative rotations, chases breakouts (e.g., BTC 3x, ETH 3x, -1x shorts).
The system continuously refines this classification based on actions taken, such as switching into riskier products or exiting in volatile conditions.
Capital-Based Adjustments
Different capital sizes demand different strategies. Vingt.io accounts for this with adaptive scaling:
<$1,000: Simplified, gas-efficient strategies — mostly stable yield or single-token exposure.
$1,000–$10,000: Diversified allocations across 4 tokens with built-in risk buffers.
$10,000+: Access to enhanced opportunities, advanced strategies, and optional capital segmentation (e.g., long-term + tactical split).
Holding Duration Preferences
Users indicate or the system infers the intended holding duration:
Short-Term (days–1 week): Prioritize momentum-based strategies, AI alerts, tactical narratives
Medium-Term (1–4 weeks): Balanced mix of strategic tokens, stablecoin buffers, optional rotation
Long-Term (1–6 months): Focus on low-risk index holdings, slow rotation, and strong-cycle alignment
This directly affects leverage exposure, entry timing, and rebalancing frequency.
Asset Bias & Thematic Interest
Over time, the AI observes which tokens or sectors a user leans toward:
BTC-heavy? Altcoin explorer? Yield farmer?
Interested in ETH L2s, AI tokens, Solana ecosystem?
Based on this, the engine fine-tunes exposure:
A BTC-preferring user in a bullish market might receive more BTX and BTC 2x vs. generic index exposure.
Interaction Feedback Loop
Every portfolio the user accepts, skips, or customizes helps train the AI:
Which allocations do they trust?
What are they likely to reject?
When do they manually adjust risk?
This ongoing feedback builds an individual AI investor profile, completely private, on-chain, and user-controlled.
Example: Personalized AI Allocation
A user logs in with the following inferred profile:
Capital: $3,500
Risk: Medium
Duration: 2 weeks
Bias: Bitcoin-centric
Market Score: 68 (early bull)
AI Output: → BTX (30%) + BTC 2x (25%) + BSK (25%) + ETX (20%) → Entry timing optimized based on RSI + whale accumulation
The portfolio is pre-loaded with rationale, expected volatility, and estimated weekly yield and ready for one-click flash-minting.
Why This Matters
User Trust: Every decision feels like it was made for them, not just a generic DeFi recommendation.
Efficiency: No need to sort through 50 tokens or 20 charts — the AI handles it.
Customization without Complexity: Advanced intelligence, clean user experience.
Future Expansion
As user data grows, this profiling engine will support:
Clustered personas (e.g., DeFi-native vs. TradFi newcomer)
Reinforcement learning: AI adapting allocation strategy based on long-term outcomes
Social-linked strategy pools (invest like influencers or whales you trust)
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