MultiEdge.ai Signal Fabric

A modern office setup with multiple curved monitors displaying financial charts, graphs, and world maps, overlooking a city skyline with illuminated skyscrapers at night. Two office chairs are placed at the desk.

AI-Curated Market Signals. Built for Quant Models & Trading Agents. Regime detection, sentiment analysis, macro indicators, and cross-asset momentum — delivered as machine-readable features via REST API, WebSocket, and webhooks. Not buy/sell alerts. Signal infrastructure.

The Problem: Your Quant Team Shouldn’t Be a Data Engineering Team

For Quantitative Trading Firms:

Building signal pipelines for each new data source requires a dedicated data science team
Maintaining quality control across dozens of signals is resource-intensive and error-prone
Regime changes cause strategy degradation — but manual regime detection is slow
Alternative data integration (sentiment, satellite, web traffic) requires specialized NLP/ML expertise

For Fintech Platforms Building AI Agents:

Generic market data APIs (Polygon, Finnhub) give you raw data, not processed alpha signals
No standardized way to feed market regime context into agent decision-making
Building signal infrastructure distracts from your core product

Five Signal Engines – Five AI Engines. One Unified API.

Engine 1: Regime Detector (HMM/LSTM)

What it does: Classifies the current market into one of four states — Bull, Bear, Crisis, or Mean-Reversion — with probability distributions and confidence intervals. Retrained monthly on 20+ years of S&P 500 data.

Inputs: S&P 500, VIX, 10Y-2Y yield spread, high-yield spreads, credit default swaps

API Response:

{
  "timestamp": "2026-03-21T13:45:00Z",
  "regime": {
    "bull": 0.72,
    "bear": 0.15,
    "crisis": 0.03,
    "mean_reversion": 0.10
  },
  "confidence": 0.85,
  "regime_duration_days": 47
}

Use case: Dynamically adjust strategy exposure based on regime state. Reduce equity allocation when crisis probability exceeds 15%. Pause momentum strategies during mean-reversion regimes.

Latency: <2 minutes end-to-end | Update frequency: Real-time

Engine 2: Sentiment Analyzer (LLM-Powered NLP)

What it does: Ingests earnings call transcripts, news articles, SEC filings, and social media — then produces per-symbol sentiment scores (-1 to +1), momentum (rate of change), and key theme extraction. Powered by fine-tuned LLM on a financial news corpus.

API Response:

{
  "symbol": "NVDA",
  "sentiment_score": 0.78,
  "sentiment_momentum": 0.12,
  "sources_analyzed": 47,
  "key_themes": ["AI demand", "data center growth", "China exposure"],
  "confidence": 0.91
}

Use case: Feed sentiment scores as features into factor models. Trigger alerts when sentiment momentum crosses ±0.6. Track theme rotation across sectors.

Latency: <3 minutes | Update frequency: Real-time (news-driven)

Engine 3: Macro Signal Engine

What it does: Produces 10+ core macroeconomic indicators: leading indicators (PMI, housing starts, jobless claims), yield curve analysis, inflation surprises, central bank policy probabilities, and currency strength indices.

API Response:

{
  "macro_environment": "expansionary",
  "yield_curve_slope": 0.45,
  "inflation_surprise": -0.2,
  "fed_hike_prob_60d": 0.23,
  "recession_prob_12m": 0.18
}

Use case: Overlay macro regime on sector rotation models. Adjust bond/equity allocation based on yield curve slope. Feed recession probability into risk management systems.

Latency: Morning update (daily batch) | Data sources: FRED, World Bank, ECB (free)

Engine 4: Cross-Asset Momentum

What it does: Multi-timeframe momentum scores (1d, 5d, 21d, 63d, 252d) across equities, bonds, commodities, FX, and crypto. Includes relative strength rankings, sector rotation signals, and risk-on/risk-off indicators.

API Response:

{
  "symbol": "SPY",
  "momentum_1d": 0.02,
  "momentum_5d": 0.08,
  "momentum_21d": 0.15,
  "momentum_63d": 0.22,
  "momentum_252d": 0.35,
  "rank_percentile": 87,
  "sector": "broad_market"
}

Use case: Feed multi-timeframe momentum into trend-following strategies. Identify sector rotation inflection points. Combine with regime detector for regime-aware momentum.

Latency: <1 second | Update frequency: Real-time

Engine 5: Signal Fusion & Quality Engine

What it does: Ensembles all raw signals into a single composite score per symbol — with dynamic weighting based on historical performance. Continuously tracks Sharpe ratio, information coefficient, and turnover per signal. Auto-disables degraded signals.

Composite Signal Response:

{
  "symbol": "AAPL",
  "composite_signal": {
    "score": 0.68,
    "confidence": 0.82,
    "components": {
      "regime":    { "state": "bull", "probability": 0.72, "weight": 0.30 },
      "sentiment": { "score": 0.78, "sources": 47,        "weight": 0.25 },
      "momentum":  { "score_21d": 0.15, "percentile": 87,  "weight": 0.25 },
      "macro":     { "environment": "expansionary",         "weight": 0.20 }
    },
    "interpretation": "Strong bullish signal driven by regime (bull market) and high sentiment. Momentum confirming uptrend."
  },
  "backtest_performance": {
    "sharpe_ratio_6m": 1.42,
    "information_coefficient": 0.18,
    "win_rate": 0.64
  }
}

Quality auto-disable rules:

Sharpe < 0.5 for 2 consecutive months → flagged for review
Information Coefficient < 0.05 for 3 months → auto-disabled
Turnover > 100x/year → flagged as overfit

Developer Experience – Production-Ready in Minutes, Not Months

Delivery Methods

REST API	WebSocket (Real-Time)	Webhooks
Azure API Management	Azure SignalR Service (WSS)	Azure Event Grid
6 core endpoints	Subscribe to specific channels	Push notifications
API key + OAuth 2.0	`wss://stream.multiedge.ai/v1/signals/live`	Regime change alerts, sentiment breaches

Use Cases by Persona – Who Uses MultiEdge Signal Fabric?

Quantitative Hedge Funds

Job to be done: “Enrich my quant models with diverse alpha signals without building a data science team for each source.”

Feed regime probabilities into dynamic allocation models
Overlay sentiment momentum on existing factor portfolios
Monitor macro indicators for strategy regime-switching
Value: 10x faster signal integration vs. building in-house

Fintech Developers Building AI Agents

Job to be done: “Give my trading agent real-time market context without building signal infrastructure.”

Plug regime + sentiment into LLM-based trading agents
Use the composite signal as a decision feature in RL training environments
Stream signals via WebSocket into event-driven architectures
Value: Plug-and-play signal layer — ship your product, not a data pipeline

Asset Managers

Job to be done: “Dynamically adjust portfolio exposure based on market regime without manual monitoring.”

Automate risk-on / risk-off allocation shifts using regime detection
Track sector rotation momentum for tactical allocation
Integrate macro signals into investment committee dashboards
Value: Regime-aware portfolio adjustments, automated

Systematic Traders

Job to be done: “Get multi-timeframe momentum across asset classes to expand strategy capacity.”

Cross-asset momentum rankings (equities, bonds, FX, crypto, commodities)
Relative strength screening across 5 timeframes (1d → 252d)
Combine momentum with regime filter for regime-aware trend following
Value: Multi-timeframe, multi-asset momentum — pre-computed, quality-tracked

Why Not Bloomberg? – 10x Cheaper. API-First. No Terminal Lock-In.

Competitive Comparison Table

Dimension	MultiEdge Signal Fabric	Bloomberg Terminal	Refinitiv Eikon	RavenPack	Quandl / Nasdaq Data Link
Pricing	$0–$2,499/mo	$24,000/year/seat	$20,000/year/seat	$20K–$100K/year	$5K–$50K/year
Delivery	REST API, WebSocket, SDK	Terminal application	Terminal + API	API	API
Signal processing	Pre-processed, model-ready	Raw + some analytics	Raw + some analytics	News sentiment only	Raw data, no signals
Regime detection	✅ HMM/LSTM, 4-state	❌	❌	❌	❌
Customization	Client-specific signal blending	One-size-fits-all	Limited	Limited	Data marketplace
Quality tracking	Sharpe, IC, auto-disable	Manual	Manual	Proprietary	None
For quant models	Designed for it	Bolted on	Bolted on	Partially	Raw data only
Free tier	✅	❌	❌	❌	Limited

Mid-tier funds can’t afford a $500K–$1M/year signal team. MultiEdge gives you institutional-quality signals for the cost of one Bloomberg seat — with API-first delivery designed for quantitative workflows.

FAQ

Q: Is MultiEdge a buy/sell signal service?
A: No. MultiEdge delivers machine-readable signal features (regime state, sentiment scores, macro indicators, momentum rankings) designed as inputs to your own quantitative models or AI agents. We provide the features — you make the decisions.

Q: What data sources do you use?
A: Equities pricing from Polygon.io and Finnhub, macroeconomic data from FRED/World Bank/ECB, news sentiment from Finnhub News and NewsAPI, social sentiment from Reddit and X APIs, plus alternative data sources (earnings calendars, web scraping). All data is normalized into a unified schema.

Q: How is this different from a raw market data API like Polygon or Finnhub?
A: Raw data APIs give you OHLCV bars and tick data. MultiEdge processes that raw data through five AI engines (regime detection, sentiment analysis, macro analysis, momentum scoring, signal fusion) and delivers pre-computed, backtested alpha signals ready for consumption by your models. We’re a signal layer on top of raw data.

Q: How do you prevent overfitting in your signals?
A: Every signal is validated using walk-forward analysis, combinatorial purged cross-validation (CPCV), and monitored with rolling Sharpe ratios and information coefficients. Signals that degrade below thresholds are automatically flagged or disabled.

Q: Can I create custom signal blends?
A: Yes, on the Enterprise tier. You can define custom weighting schemes across our signal engines (e.g., 40% regime, 30% sentiment, 20% momentum, 10% macro) and create proprietary composite signals accessible via your API key.

Q: What’s the latency?
A: Real-time price-driven signals (momentum): <1 second end-to-end. Regime detection: <2 minutes. Sentiment (news-driven): <3 minutes. Macro indicators: daily morning batch. REST API query response: p95 <200ms.

Q: Is this available on Azure Marketplace?
A: Yes. MultiEdge Signal Fabric is a transactable SaaS offer on Azure Marketplace. It’s MACC-eligible, meaning your existing Microsoft Azure Consumption Commitment credits apply. Enterprise procurement teams can purchase through their existing Azure billing relationship.

Q: Do you offer an SLA?
A: Professional tier: 99.5% API uptime. Enterprise tier: 99.9% uptime with dedicated support and contractual SLA. Multi-region deployment (Southeast Asia, US East, EU West) ensures global availability.

Q: What if I only need one type of signal?
A: The Explorer (free) and Starter ($199/mo) tiers include 5 and 20 signals respectively — you choose which ones. You don’t pay for signals you don’t use. Upgrade to Professional for full access to all signal types.

Q: How do I get started?
A: Sign up for the free Explorer tier — no credit card required. You get an API key in under 2 minutes, 100 API calls/day, and access to 5 signals with 15-minute delayed data. Integrate using our Python or C# SDK.