Our Technology Engine
The heart of Moriarty Trade is a multi-layer AI platform that collects billions of market signals, processes them in real time, and turns them into profitable decisions.
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How it works — 4 steps
1. Data collection
Order books, social networks, on-chain, macro-news — everything flows into our global crawler 24/7.
2. Cleaning & normalization
ML filters remove noise and anomalies; aggregate latency < 60 ms.
3. Model ensemble
LSTM + Transformer + GBM find patterns on 15 PB of history.
4. Execution
Risk-core module checks the signal and sends the order via low-latency API.
Platform architecture
The diagram below shows how data goes from ticker to your trade. All computation is distributed among four geo-clusters.
Key modules
Latency‑Aware Router
Selects the best liquidity provider by ping+depth, reducing slippage by 17%.
Anomaly Shield
Isolation Forest instantly cuts off flash-crash data, reducing false signals by 22%.
Cross‑Chain Liquidity Scanner
Tracks spot and derivatives in 8 L2 networks, opening arbitrage windows.
Explainable‑AI Console
Shows the trader which factors influenced the model decision.
Dynamic Position Sizer
Auto-calculates order volume based on market kurtosis and available margin.
Auto‑Strategy Compiler
Converts YAML strategy descriptions to bytecode without cluster restart.
Realtime Feature Store
1200+ features, updated every second. RedisCluster cache < 10 ms.
LLM‑Sentiment Oracle
GPT-4 analyzes 2 million tweets/day and computes the asset"emotions" index.
Adaptive Risk Matrix
Risk coefficient recalculated 50×/sec based on volatility and liquidity.
Step by step: How a trade is born
Multi-source data
• Order-book L2 (Binance, Bybit, OKX) in stream 50 ms
• On-chain metrics (gas, active wallets)
• 2M+ social posts/day via LLM-Sentiment
• Macro tracker (DXY, S&P 500 futs)
Cleaning and feature engineering
• Isolation Forest removes flash-noise
• 1,247 features into Redis-Feature-Store (< 12 ms)
• Z-score normalization catches liquidity spikes
Model ensemble
• LSTM catches the order of candles
• Transformer reads news/tweet context
• Gradient Boosting retrains on last 10 days
Bayesian Selector gives weights based on hour volatility
Risk-core
• Value-at-Risk calculated 50×/sec
• Dynamic-Position-Sizer sets volume
• If VAR < threshold — green light for execution
Low-latency execution
• REST fallback < 150 ms if WebSocket drops
• 87% of orders hit the first price level
Self-learning
• After closing the deal, the whole track (state-action-reward) is logged
• Night"Replay Trainer" recalculates weights; fresh models go to Prod without downtime (A/B canary release)
Live example: 14 seconds from signal to profit
00 : 00 : 00
L2 Order-book BTC/USDT shows bid spike +1,800 BTC in 90 ms.
00 : 00 : 03
LLM-Sentiment catches a series of tweets from Glassnode about BTC outflow from exchanges.
00 : 00 : 05
Model ensemble raises"long-probability" to 0.83 (threshold 0.75).
00 : 00 : 06
Risk-core calculates 0.37 BTC volume (VaR 1.4%).
00 : 00 : 07
Smart-Router chooses Bybit (lower spread), sends limit order.
00 : 00 : 14
Price +0.42% — TP hit, profit +0.0016 BTC, log sent to Replay Trainer.
Bank-level security
AES-256 Encryption
All user data is encrypted"at rest" and"in transit".
RBAC + MFA
Zero rights by default and mandatory two-factor authorization.
Zero‑Trust Network
Each service authenticates on every request; there are no"trusted zones".
Real‑Time Threat Detection
SIEM platform analyzes logs in stream and alerts the SOC team < 30 sec.
Numbers you can trust
< 70 ms
Average"signal → order" latency
87 %
Orders hit the first price level
15 PB
Data for model training
99.97 %
Inference-cluster uptime for 12 months
Frequently Asked Questions
What algorithm is at the heart of predictions?
LSTM + Transformer + Gradient Boosting ensemble with Bayesian Hyper-search.
How many servers does a client need?
None — everything is hosted on our clusters, you connect via API or enable copytrading.
How often are models retrained?
Base weights update monthly, online fine-tune — in real time.
Can I connect my own data?
Corporate clients get an SDK for ingesting private datasets.
What is the average API call latency?
p99=42 ms in EU datacenters.
Where are the servers located?
Frankfurt, Amsterdam, Virginia, Tokyo — 4 geo-clusters.
Are futures supported?
Yes. Binance, Bybit, OKX USDT-M and COIN-M contracts and others.
Minimum deposit?
$100 to start, ideally ≥ $300.
Can I export logs?
REST endpoint/v1/trades/export returns CSV.
Is there a white-label?
Yes, corporate license and 99.99% SLA.
What if the exchange is unavailable?
Fail-over switches WebSocket to backup in < 3 sec.
Ready to experience the power of technology?
Connect to Moriarty Trade and let our AI engine turn data into profit today.
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