Intelligence Infrastructure for Global Energy & Macro Markets
Structured data and analytics infrastructure for energy intelligence. Domain-trained models extract signals from unstructured sources - we inform decisions, not predict outcomes.
"OPEC+ cuts production targets by 500K bpd as Brent crude futures surge on Nord Stream pipeline disruption. EU energy ministers to convene emergency session..."
Data Engineering Infrastructure for Energy Intelligence
Production-grade pipelines ingest, normalize, and structure global energy data across open-source and institutional datasets.
Data Sources
- EIA
- OPEC
- IEA
- Platts
- S&P Global
Ingestion
- DLT
- Python
- API Connectors
- GitHub Actions
Normalization
- DuckDB
- SQL Transforms
- Schema Validation
- Quality Checks
Feature Layer
- Time Series
- Aggregates
- Calculated Fields
- Delta Updates
Data Coverage
| Category | Sources | Update Frequency |
|---|---|---|
| Crude Oil | EIA, IEA, OPEC | Daily |
| Natural Gas | EIA, Platts | Daily |
| Petroleum Flows | EIA, Customs Data | Weekly |
| Production Data | OPEC, IEA | Monthly |
Built for Production Scale
GitHub-orchestrated pipelines with DuckDB for analytical processing. DLT (data load tool) handles incremental loading and schema evolution. All transformations version-controlled and reproducible.
Physical Tightness Index (PTI)
A structured measure of supply-demand imbalance derived from physical market signals. Not a prediction - a quantified snapshot of market conditions.
Raw Data Layer
Structured time series from authoritative sources
Feature Engineering Layer
Transform raw signals into market-relevant indicators
Modeling Layer
Time series + ML models for tightness quantification
PTI System Architecture
United States as the Global Oil Driver
US-specific PTI modeling using EIA datasets, WTI pricing, and production + inventory signals. The world's largest oil producer deserves dedicated infrastructure.
US PTI Forecast
30-Day HorizonForecasting Engine
Multi-horizon forecasts using ensemble methods. 7-day, 30-day, and quarterly projections with confidence intervals.
Simulation Scenarios
What-if analysis for production changes, inventory shifts, and policy interventions. Scenario comparison tools.
WTI Integration
Direct mapping between PTI movements and WTI pricing dynamics. Historical correlation analysis.
Primary Data Sources
Global Petroleum Tightness
Extends PTI framework globally. Incorporates OPEC production data, international supply chains, and regional pricing signals.
Regional Tightness Index
Global Data Integration
- OPEC+ production quotas and compliance
- International Energy Agency (IEA) reports
- Regional pricing benchmarks (Brent, Dubai, Urals)
- Trade flow data and shipping patterns
- Geopolitical event mapping
Regional Modeling
Structured News Intelligence - Not Just LLM Summaries
Custom-trained transformer models extract structured signals from unstructured news. Hybrid NLP combines transformers with traditional methods for accuracy and speed.
NLP Pipeline
Custom Hugging Face Models
- Fine-tuned on 2M+ energy & macro documents
- Domain-specific entity taxonomy (247 types)
- Multi-task learning: NER + classification + sentiment
- Hybrid approach: transformers + rule-based
Performance
{
"source": "Reuters",
"timestamp": "2026-04-03T14:23:47Z",
"entities": [
{"text": "OPEC+", "type": "CARTEL", "confidence": 0.98},
{"text": "500K bpd", "type": "PRODUCTION_METRIC", "value": 500000},
{"text": "Brent crude", "type": "COMMODITY", "confidence": 0.97}
],
"classification": {
"primary": "SUPPLY_SHOCK",
"secondary": ["POLICY_CHANGE", "PRODUCTION_CUT"],
"confidence": 0.94
},
"sentiment": {
"overall": "BEARISH_SUPPLY",
"price_direction": "BULLISH",
"impact": "HIGH"
}
}LLM-Powered Intelligence Workflows
Fine-tuned open-source LLMs with domain-specific training. Proprietary datasets map news events to actual market reactions.
Fine-Tuning Pipeline
Proprietary Dataset
News articles mapped to actual market reactions. Timestamps synchronized with pricing data for causal inference.
Fine-Tuning Methods
Inference Engine
vLLM for high-throughput, low-latency inference. Batching and continuous batching for efficiency.
Applications
- Event impact quantification
- Market reaction prediction (analytics, not trading signals)
- Policy document summarization
- Scenario generation
- Historical pattern matching
Model Performance
Market-Aware Training
Unlike generic LLMs, our models understand the temporal relationship between news and market movements. Training data includes price action context.
Example Query
"Analyze the market impact of OPEC+ production cuts announced in March 2023"
Historical analysis shows OPEC+ production cuts of 500K+ bpd correlate with 3-7% WTI price increases within 10 trading days. March 2023 cut led to 5.2% increase. Supply-side shocks typically maintain elevated prices for 4-6 weeks before mean reversion.
Ask the Market
RAG-based system with continuously updated knowledge base. Context-aware answers backed by structured data, not hallucinations.
What's the current US PTI trend and what's driving it?
US PTI is currently at 67.2 (up 4.3% WoW). Key drivers:
- Inventory drawdown: -2.1M barrels vs. expected -1.4M
- Refinery utilization: 92.3% (seasonal high)
- Production flat at 13.2M bpd
Compare this to the same period last year
PTI is 12.3 points higher YoY. Last year same week was 54.9. Primary difference: inventory levels 8% lower this year, demand 3% higher.
Capabilities
- Query energy market conditions
- Get historical context
- Generate custom charts
- Compare time periods
- Explain signal changes
Data-Grounded Responses
All responses backed by actual data. Citations to source tables, update timestamps, and confidence intervals included.
Knowledge Base
Custom Filtering
Filter by time period, region, commodity type, or data source. Relevance logic prioritizes recent data and high-quality sources.
Expanding Intelligence Coverage
Upcoming modules extend coverage into political signals and proprietary data sources
Political Signal Tracking
Map political actions to market impact
Track Politicians & Policy Makers
- Congressional votes on energy legislation
- OPEC+ ministerial statements and decisions
- Central bank commentary on inflation/energy
Link to Market Impact
- Policy announcements -> crude price movements
- Regulatory changes -> sector equity performance
- Geopolitical tensions -> volatility spikes
Note: Political tracking focuses on public statements and voting records. No private communications. All data from publicly available sources.
Data Coverage Expansion
Adding proprietary and closed-source data feeds
Paid Datasets
- S&P Global Platts energy data
- Bloomberg commodity feeds
- Refinitiv shipping and trade flow data
- Satellite imagery for infrastructure monitoring
Impact on Signals
- Higher granularity: regional -> terminal-level data
- Real-time updates: daily -> hourly where available
- Alternative data: shipping AIS, satellite, weather
Roadmap
We Don't Predict. We Inform.
QuantBridge is an intelligence infrastructure, not a prediction platform. We provide analytics, signals, and decision support - not trading recommendations.
Structured Data
We extract and structure market data. Analysis is descriptive, not prescriptive. Users make their own decisions.
Transparency
All data sources cited. Model confidence scores exposed. Methodology documented. No black boxes.
Decision Support
Tools for analysis, not trading signals. Users integrate our data into their own workflows and models.
Our Philosophy
Markets are complex adaptive systems. No model can consistently predict outcomes. What we can do is provide clean, structured, and timely intelligence that helps sophisticated users make better-informed decisions.
We're infrastructure for analysts who understand markets - not a magic prediction engine.
QuantBridge provides data and analytics infrastructure. Nothing on this platform constitutes financial advice, trading recommendations, or investment guidance. All users are responsible for their own decision-making. Past performance is not indicative of future results. Markets involve risk.
Build on Signals, Not Noise
Join institutional investors, hedge funds, and research teams using QuantBridge to extract intelligence from global markets.