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View case
Oil Market Intelligence
Price data meets news, weather and policy signals.
The challenge
Oil prices react to news, weather and government decisions, but analysts track those feeds separately and struggle to tell which events actually matter, and why.
What we built
A market research application that combines oil price data with news, weather and government event feeds. An implemented rule-based classifier assesses each event for oil market relevance, potential direction and confidence, and keeps source references so users can examine the evidence.
The AI layer
- A foundation for future predictive AI.
- Experimental event signals are deliberately kept separate from automatic forecast changes.
How it works
The workflow, step by step.
- 01Feeds collected
- 02Events classified
- 03Relevance, direction and confidence scored
- 04Evidence linked
- 05Analyst reviews
Architecture
How the pieces connect.
Inputs
- Oil prices
- News
- Weather
- Government events
The system
- Price data
- Event feeds
- Event classifier
- Evidence trail
- Signal separation
AI
- A foundation for future predictive AI
- Experimental event signals are deliberately kept separate from automatic forecast changes
People
- Analyst
- Research lead
Outputs
- Scored event stream
- Evidence trail
- Research views
Functional architecture. Integrations and hosting are tailored to each client's environment.
Modules
Everything in one system.
01Price data
Oil price history alongside events.
02Event feeds
News, weather and government events in one stream.
03Event classifier
Relevance, direction and confidence for each event.
04Evidence trail
Source references kept for every signal.
05Signal separation
Experimental signals kept apart from forecasts.
Interface preview
What your team would see.
Illustrative interface · sample data
Who uses it
Built around real roles.
Analyst
Reviews ranked signals and evidence.
Research lead
Decides what informs the house view.
A storm warning, a producer statement and a refinery news story arrive within an hour. Each is scored for relevance and likely price direction, with its source attached, so the analyst reviews three ranked signals instead of three hundred headlines.
Build your version
Start here, extend further.
Capabilities we can build on this foundation for your version of the system.
- Model-driven price forecasts with backtested accuracy
- Tanker and shipping data
- Refinery outage tracking
- Morning analyst briefings generated automatically
- Alerts when high-confidence events break
Questions
What clients ask us.
Does it change forecasts automatically?
No. Experimental event signals are deliberately kept separate from automatic forecast changes.
Can we see why an event was scored?
Yes. Source references are kept for every event so users can examine the evidence.
Can you build a version of this for our business?
Yes. Every system starts with a discovery conversation about your workflow, data and goals, and we adapt the design to fit. Most engagements produce a working, testable system within a few weeks to a couple of months, depending on scope.
Can it integrate with the systems we already use?
Integration with existing tools such as ERPs, accounting packages, databases and document stores is scoped during discovery, so the system fits around how you already work.
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