AI-Powered Trading Intelligence

Every Signal Comes With a Reason

Multi-expert AI analyzes 17 data dimensions in real-time. Each signal includes a full causal reasoning chain — not just "buy" or "sell", but exactly why.

Early Access · First 100 members get 2 weeks free
Hyperliquid Ready · On Stack
17
Data Dimensions
4
AI Experts
70+
Coins Watched
10K+
Anomalies / Day
40+
Signals / Day
the era · 2026

trading in 2026 —
you are as strong as
your AI agent.

the market compounds at machine speed. a single human, no matter how sharp, cannot cover a live crypto tape alone anymore. the edge has moved — from screen-time to agent-time.

we are
01
Signals
reasoning-grade setups. every call comes with the why.
02
AI Agent
your private analyst. watches the tape 24/7.
03
Auto Trading
hands-off execution on hyperliquid.
→ three pillars · one platform
Last 5 Successful Signal Hits

What You Get

Real verified signals from the past 7 days — every one hit its take-profit target.

POWERED BY HYPERLIQUID · FIRST-CLASS INTEGRATION

Arm it. Go Live. Trade Real Markets on Hyperliquid.

One hold of the button. We arm the risk controls, sign the agent, and your signals start executing on HyperLiquid in under a second.

  • Wallet Connected
  • Network: HL Arbitrum
  • Risk Caps Set
  • Auto SL / TP
  • Safety-Halt Ready
  • Signal Cosign
Hold the button for 1.2 seconds to simulate going live on Hyperliquid See how it works ↗

Non-custodial — you always keep your keys.

Auto-Executed Positions STANDBY
Awaiting go-live signal...
From The Founder
The person behind the signals
Roman A.
Roman A.
/roman-rr
Microsoft Certified AI Architect · 20+ years engineering · AI / Crypto Researcher
When I started building Signals, I leaned heavily on my AI-agentic experience and LLM research — every decision a model makes should be inspectable, every signal should come with a causal reason chain, not a black-box score.
What Sets Us Apart

Intelligence, Not Guesswork

Every signal is backed by a multi-dimensional analysis pipeline that processes funding rates, order flow, technical structure, and on-chain data simultaneously.

🧠
Multi-Expert Consensus
Three specialized AI experts analyze independently. Signals require agreement — conflicting views are flagged or filtered.
🔗
Transmission Chains
Every signal includes 2-4 causal reasoning steps. See exactly which data points led to the trade.
💰
Paper Trading P&L
Every signal is a real trade on a virtual account. The system auto-tightens risk when drawdown increases.
🛡
Dynamic Risk Control
Confidence-based leverage caps, ATR-calibrated stop losses, and automatic regime detection.
🔍
Market Sentinel
17 anomaly triggers across 6 groups: volume, positioning, price, cross-asset, microstructure, and Deribit options. Event-driven, every minute.
✅
Auto-Verification
Every signal is verified at the AI-chosen timeframe. TP/SL monitoring runs every minute.
Example: Transmission Chain
1
Funding Rate Extreme
ETH funding: -0.042% (8h) — 3.2σ below baseline
Shorts are heavily crowded and paying a premium. This level of negative funding has preceded squeezes in 67% of historical cases.
2
Volume Divergence
Spot buy volume +340% vs 7d avg, futures volume flat
Smart money accumulating spot while futures traders remain short. Volume divergence confirms conviction.
3
Liquidation Cluster
$48M short liquidations between $3,420-$3,460
Dense cluster of short stop losses just above current price. A move into this zone would trigger cascading liquidations.
4
Entry Signal
Entry: $3,385 | SL: $3,310 | TP: $3,520 | R:R 1.8:1
Bullish entry with tight risk below support. SL respects ATR(14) floor. TP targets the liquidation cluster zone.
Always Watching

17 Triggers. 6 Groups. Every Minute.

The sentinel scans 50+ perpetual markets for anomalies across six orthogonal dimensions — from order book microstructure to Deribit options flow.

Anomalies
17 triggers scan
→
Confluence
2+ groups agree
→
Trend Phase
13 detectors classify
→
Signal
3 experts merge
17
Triggers
6
Trend Voters
7
Modifiers
50+
Coins Scanned
Meet Singularity
The three states the system flows through
Chain
Pressure across time. When the same anomaly persists for minutes, it compresses into a chain.
SL TP ENTRY
Signal
The moment a chain resolves into a trade. One entry, one take-profit, one stop — released into the market.
×3
Fusion
When signals for the same coin, same direction, from different runs meet — the thesis converges.
Trigger categories — 17 detectors across 6 groups
▰▰▰▰▱ 4
Volume & Liquidity
Detects unusual volume, mass liquidations, hidden directional flow, and informed trading pressure.
volume_spikeliquidation_cascadeflow_divergencevpin_toxicity
▰▰▰▰▰ 5
Positioning
Tracks funding rate extremes, velocity shifts, post-crowding reversals, OI divergence, and basis dislocation.
funding_extremefunding_velocityfunding_reversaloi_divergencebasis_spread
▰▰▰▱▱ 3
Price Dynamics
Multi-window breakout detection catches moves at different speeds.
breakout 5mbreakout 15mbreakout 60m
▰▰▱▱▱ 2
Cross-Asset
Detects when alts decouple from BTC or capital rotates between coins.
beta_divergenceoi_redistribution
▰▰▱▱▱ 2
Microstructure
Reads the order book structure and trade intensity for early signals.
obi_imbalancetrade_arrival_spike
▰▰▰▱▱ 3
Options-Derived
Forward-looking signals from Deribit — what smart money expects to happen.
dvol_spikepc_ratio_shiftiv_skew_shift
Σ 17
Total Triggers
updated every minute
Research-Grounded

44 Scientific Methods. 53 Academic Citations.

Every algorithm is grounded in peer-reviewed research from quantitative finance, statistics, and machine learning.

📊
Position Sizing
Kelly Criterion (half-Kelly), ATR-based normalization, Turtle Traders risk model. Adaptive sizing from paper balance metrics.
Kelly 1956, Thorp 2006, Faith 2007
⚠
Anomaly Detection
CUSUM change-point, Modified Z-score (MAD), EWMA beta decorrelation, excess kurtosis, realized volatility ratio, Benjamini-Hochberg FDR.
Page 1954, Iglewicz 1993, Andersen 2003
📈
Technical Analysis
RSI, MACD, Bollinger Bands, ATR, ADX, VWAP, OLS regression + R², swing S/R, Pearson cross-asset correlation.
Wilder 1978, Appel 1979, Bollinger 2001
🤖
Multi-Expert AI
Mixture of Experts ensemble, Thompson sampling model selection, weighted composite scoring, regime-adaptive expert weighting.
Jacobs 1991, Thompson 1933, Chapelle 2011
🏦
Market Microstructure
CVD via tick rule, funding rate contrarian signals, options expiry pin risk, order book imbalance detection.
Lee & Ready 1991, Easley 2012, Avellaneda 2003
🛡
Risk Management
Balance-based regime switching, profit factor over hit rate, walk-forward paper validation.
Boyd 2017, Van Tharp 1998
How It Works

From Data to Trade in Under 3 Minutes

The system watches markets 24/7. When anomalies are detected, the full analysis pipeline fires automatically.

Market Anomaly Detected
17 triggers across 6 groups scan 50+ coins every minute — from volume spikes to options flow to order book microstructure.
17-Dimension Data Prefetch
Funding, order books, trades, TA indicators, news, on-chain flow, and smart money positioning — all in parallel.
Multi-Expert AI Analysis
Three independent experts: Technical, Flow, and Regime. No single point of failure.
Consensus & Risk Gate
Experts must agree. Confidence is weighted. Risk regime enforces leverage, sizing, and SL floors.
Signal Delivered
Complete trade setup: entry, SL, TP, leverage, position size, and the full reasoning chain.
Early Access

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📡
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