See where commodity markets are moving before the curve reflects it.
Measure futures direction using structured public signal, with transparent gaps for deeper market data.
Commodity markets are driven by multiple layers: physical conditions, sentiment, positioning and pricing.
Most systems rely on price and structured datasets. Noah measures the signal environment forming around those markets, identifying directional pressure before it is fully reflected in futures curves or positioning data.
The result is a forward signal layer that complements, not replaces, traditional market data.
Signal forms before price. Structured data confirms it later.
Noah identifies early directional pressure, fragmented information and consistency across sources — while clearly identifying where deeper market data would refine the read.
Most systems wait for the positioning data. Noah measures what's forming in the signal environment before that data is published.
Signal moves first: weather narratives, trade activity, geopolitical pressure, agricultural reporting. The futures curve and positioning data confirm what the signal already implied.
This makes Noah a forward layer, not a replacement for Bloomberg or COT data.
Six commodity-grade investigations.
What teams actually ask.
Corn futures · 21-day directional read.
What a single commodity investigation returns: a structured posture, composite score, direction, confidence and the evidence behind it.
Corn futures · 21-day directional read
Drivers
- Increasing drought signal across key regions
- Trade flow disruption indicators
- Rising consistency in agricultural reporting
Watchpoints
- Official inventory data release
- Weather pattern confirmation
- Futures curve adjustment
{ "frame": "futures_commodities", "subject": "corn futures", "decision": { "posture": "watch_upward_pressure", "composite": 63, "direction": "strengthening" }, "confidence": "moderate", "evidence_count": 19, "lane_governor": { "proxies_added": 2, "missing_lanes": [ "futures_curve", "cot_positioning", "official_inventory_data", "weather_forecast_data" ] } }
Lane Governor.
The system layer that ensures every market investigation has the right structure — with explicit gaps where specialist data is missing.
Ensure the right market structure is always considered.
Lane Governor prevents incomplete or misleading reads.
It detects the investigation type, confirms the required analytical lanes are present, adds safe public-signal proxy lanes where appropriate, and flags missing specialist data clearly in the output.
Every commodity read passes through this system before a result is returned.
What's live now. What's connecting next.
Two distinct layers, treated differently. Signal is read live across the public reporting environment. Market data is integrated through specific connectors — clearly labelled, never implied.
Read continuously.
- News and reporting
- Trade activity
- Weather narratives
- Geopolitical developments
Integrated as connectors land.
- Futures curve
- COT / fund positioning
- Options skew
- Official inventory data
- Weather forecast datasets
- Shipping flow data
No hidden assumptions. No implied data.
If a lane is not available, the system does not pretend it is. The output flags it explicitly.
- It is not simulated
- It is not approximated
- It is flagged clearly in the output
Each commodity investigation, end to end.
Routes through a futures/commodities workflow.
The system selects the commodity-specific frame — agricultural, energy, metals, soft commodities — rather than a generic investigation.
Constructs supply, demand and narrative lanes.
Each lane has its own evidence pool: production data, consumption signal, sentiment formation, geopolitical pressure.
Applies Lane Governor checks.
Confirms required lanes are in place. Identifies which specialist datasets are missing and would refine the read.
Adds proxy signal where safe.
Uses public-signal substitutes for missing lanes only when proxies are reliable. Logs each substitution explicitly.
Measures directional pressure.
Aggregates across lanes to score posture, composite, direction and confidence.
Returns structured output.
Posture, score, drivers, watchpoints, evidence count, missing lanes and audit identifier — every read.
Two ways the system handles weather.
Weather narrative is read continuously. Weather forecast data is integrated as a connector — clearly distinguished.
Reporting, commentary, emerging narrative.
Read continuously across the public signal environment — agricultural press, regional reporting, trade commentary, official statements about conditions.
Forecast models, quantitative datasets.
Integrated through specialist data connectors as they're added. Provides the precision layer that signal alone cannot deliver.
What's connecting next.
The system is built to integrate specialist market data through clearly labelled connectors. Each one will be explicit, never implied.
- Clearly connected
- Explicitly labelled
- Never implied
Where the market signal layer fits.
Built for forward market reads.
- Commodity trading
- Macro analysis
- Supply chain planning
- Agricultural forecasting
- Energy market analysis
Teams that read commodity markets.
- Traders
- Macro investors
- Commodity analysts
- Hedge funds
- Corporates exposed to commodities
How teams deploy this layer.
The curve moves when the signal becomes visible.