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Zonein AI‑Powered Dashboard

The dashboard is your command center. It turns live market, on‑chain, and social signals into clear, explainable guidance, arranged in widgets you control. Every tile draws from the same validated data and AI reasoning used across Zonein, so what you see is consistent, fast, and tied to your actual context (holdings, watchlists, and current focus). The goal is simple: fewer tabs, quicker checks, and decisions you can verify.

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From Data to Insight

Core Dashboard Features.png The dashboard subscribes to real‑time streams (prices, liquidity, transactions, social mentions) and keeps a historical baseline for comparison. As updates arrive, lightweight jobs enrich them with labels (token metadata, contract type, exchange addresses) and compute reusable metrics (e.g., 1‑hour whale netflow, pool depth at fixed slippage, 24‑hour sentiment delta). When a widget needs an answer, the system assembles only the relevant slice of data—scoped to your portfolio, watchlists, and selected timeframe—then applies a reasoning step that compares current readings to recent history. Recommendations are ranked by a graph‑based engine that measures similarity across users, assets, and opportunities. Three signals drive this ranking:
  • User↔User similarity (behavioral alignment and risk profile).
  • User↔Content similarity (fit between your profile and a specific opportunity).
  • Content↔Content similarity (related or diversifying ideas).
Under the hood, events are turned into vectors (normalized features like volatility, depth, social velocity, smart‑money flow). Cosine similarity and behavioral correlation find close matches; business rules add risk rails (liquidity floors, spread checks, concentration caps) and urgency (time‑sensitive unlocks, policy changes). Results arrive as a TL;DR first, with numbers, sources, and a confidence label available on demand. Typical latencies: sub‑second for live tiles; longer research streams progressively with a summary up front. How the Recommendation Engine Works (1).png

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What You Use

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Portfolio Overview

A unified view across chains with real‑time balances, P&L/ROI, historical charts, and allocation by chain/token/sector. Quick actions let you pivot to research or execution. Optional cost basis and notes are supported.

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Copy Trading

A ranked view of consistently successful wallets and strategies, with transparent performance stats (PnL, win rate, typical hold time). Start in paper mode, set allocation and stop‑loss limits, then move to live only if it meets your criteria.

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Market Intelligence

AI‑curated trends and regime signals: trending tokens, short‑horizon price forecasts with confidence ranges, and a news summary filtered to what can move your positions. Opportunity cards explain “why now” in one line, with sources linked.

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Social Analysis

Credibility‑weighted sentiment from Twitter/X, Reddit, and key Discords. Tokens are grouped by mood shift; opening a token shows top drivers, recent velocity, and whether chatter looks organic or coordinated.

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Events Calendar

The dates that matter: token unlocks and vesting, major protocol upgrades, listings/migrations, governance deadlines, and notable community events. Each entry includes timing, expected impact (when available), and links to sources.

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Yield Opportunities

Personalized DeFi ideas based on what you hold. APY/TVL/depth and volatility notes are shown side‑by‑side. An IL estimator flags ranges under realistic assumptions. Auto‑compound and reminders are optional.

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Global Controls

  • Layout: drag‑and‑drop, save per device; light/dark themes.
  • Data preferences: filters for chains, sectors, and minimum liquidity.
  • Alerts: rules on metrics (e.g., “whale_netflow_1h < −$500k for TOKEN”), with cool‑downs to avoid noise.
  • Feeds: live price ticks, curated news, social signals, and whale alerts that match your filters.

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Personalization & Models

Personalization is data‑driven and privacy‑aware. The dashboard learns from interactions (what you open, mute, pin), portfolio composition, and outcomes (what you followed or ignored). It does not collect full browsing history. A graph engine combines:
  • Behavioral learning (which ideas you act on vs. skip).
  • Risk profiling (drawdown tolerance, preferred horizons, concentration).
  • Context awareness (market regime, volatility states, liquidity conditions).
Similarity is computed over vectors built from:
  • On‑chain: transfers, DEX trades, staking, governance.
  • Market: price/volume, depth at slippage, spreads.
  • Social: sentiment velocity, influencer coverage.
  • Smart‑money: cluster flows, copycat pressure, exchange transfers.
The ranking engine blends these signals, applies quality filters (liquidity floors, data freshness), and diversity controls (avoid over‑concentration). Advanced capabilities include predictive analytics (short‑term movement estimates with error bands), cross‑chain intelligence (bridge flows, arbitrage hints), and real‑time adaptation (fast decay on stale signals). Explanations remain simple: inputs used, method notes, and confidence.