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ZoneIn Roadmap

ZoneIn is building toward a future where the best trading intelligence is accessible to everyone — not locked behind institutional walls — and where agents can act on that intelligence autonomously, transparently, and with verifiable track records. Here’s where we are and where we’re going.

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What’s Live Now

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Intelligence Layer

  • AI Dashboard — Real-time composite signals across Perp, Spot, HIP-3, and Prediction Markets on Hyperliquid and Polymarket
  • Smart Money Telemetry — Continuous profiling of high-conviction wallets by realized performance, multi-timeframe consensus, behavioral clustering, and similarity detection
  • Signal Fusion Engine — Adaptive weighting of SM telemetry + multi-timeframe TA + derivatives flow into a single decomposable conviction score
  • Token Detail Pages — OHLC charts with SM strength overlay, trade flow bubbles, SM liquidation heatmap, funding rate histograms, derivatives dashboard, technical gauges
  • Position Graphs — Interactive bipartite graphs showing the full flow topology between SM wallets and their positions (Perp, Spot, PM, HIP-3)

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Execution Layer

  • Trading Agents — Strategy presets + custom triggers, LLM/Rule/Hybrid/Ensemble policies, non-custodial vaults with gas-sponsored USDC bridging on Hyperliquid
  • HITL Trade Plans — Full-evidence trade proposals with one-tap Telegram approval
  • Backtesting — Historical simulation against real signals and OHLC prices
  • Continuous Learning — Daily feedback loop: trade attribution, failure pattern detection, prompt context enrichment, threshold self-tuning

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API & Integrations

  • REST API at mcp.zonein.xyz/docs — Full programmatic access to signals, SM data, agents, and backtesting
  • MCP Protocol — AI assistant integration for OpenClaw, Claude Desktop, and any MCP-compatible client
  • Telegram Bot — Trade notifications and HITL approval with inline buttons

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What’s Next

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Deeper Intelligence

  • Expanded SM wallet coverage — Continuously growing the labeled wallet set with automated discovery of high-performing addresses
  • Sentiment and narrative signals — Integrating social and news sentiment as an additional signal source in the fusion engine
  • Cross-venue mispricing detection — Identifying pricing inefficiencies between Hyperliquid perps, HIP-3 DEXes, and spot markets
  • Enhanced TA models — Adding volatility regime detection and adaptive indicator weighting per market condition

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Smarter Agents

  • RL-based policies — Reinforcement learning agents trained in Gym-compatible trading environments, learning from market feedback loops
  • Multi-agent orchestration — Multiple agents with different strategies sharing intelligence and coordinating execution
  • Strategy marketplace — A curated ecosystem where agent configurations can be shared, backtested, and deployed — with verifiable performance on-chain
  • Automated threshold optimization — Agents that self-tune their trigger conditions based on rolling backtest results

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Web3 Trust & Payments

  • ERC-8004 Verifiable Agent Reputation — Every agent gets an on-chain identity with auditable performance history. Portable reputation that follows agents across platforms — solving the trust gap in copy-trading and alpha bots
  • x402 Pay-Per-Request — Micropayments for premium signal data. No subscriptions — pay per API call with stablecoin settlement. Signal quality determines revenue in a true intelligence marketplace

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Expanded Coverage

  • New on-chain venues — As new high-volume venues emerge in the on-chain economy, ZoneIn will expand signal coverage and agent execution support
  • Additional prediction market platforms — Beyond Polymarket, tracking top traders across emerging prediction market venues
  • Cross-chain smart money — Extending wallet profiling and signal fusion to smart money activity across multiple chains

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Guiding Principles

Every addition to the roadmap must pass two tests:
  1. Does it compress the trader’s OODA loop? If it doesn’t help traders observe faster, orient better, decide smarter, or act quicker — it doesn’t ship
  2. Can it be explained clearly? If a feature’s value can’t be articulated in one sentence, it needs more thought before building