Reinventing Commodities StorageRisk Intelligence
Trust for Physical Commodities — Enforced by Design
Sphere is an AI risk intelligence platform that anchors physical storage locations and inventory to verified geospatial proof — enabling defensible risk, credit, and trading decisions before exposure is taken.
Used by banks, traders, insurers, and storage operators to align decisions to physical reality.
- Physical reality is the source of truth
- Verification is enforced, not discretionary
- Proof is shared mathematically, without raw data leaving the platform
Where Commodity Risk Breaks Down
Commodity risk fails when physical reality, documents, and decisions drift apart.
- Inventory exists on paper — but not where it is assumed to be
- Controls are declared — but not independently verified
- Evidence is reused, reinterpreted, or detached from its location
- Risk is assessed after exposure, not before financing is committed
This is where fraud, disputes, and silent risk accumulation begin.
Sphere is built to close this gap at the source — before financing is committed.
One Platform. Two Perspectives. Shared Confidence.
Sphere creates a single, shared risk baseline across the storage ecosystem — aligned to physical reality and enforced through verification
For Cargo Owners, Traders & Banks
- Defensible risk decisions before financing and trading are committed
- Reduced collateral leakage and double-pledging risk
- Faster credit, trading, and insurance approvals
For Storage Operators
- Clear, AI-defined verification requirements
- Control maturity demonstrated through execution — not assertions
- Operational integrity becomes a commercial advantage
From Physical Reality to Defensible Trust
Sphere binds physical reality to verifiable truth — once, at the source, and enforced over time
Anchor the Location
Each storage site is anchored to immutable geospatial boundaries and physical constraints. Risk begins with where assets physically exist — not documents or declarations.
Model Risk Before Controls
AI models assess inherent risk using location, cargo type, environment, and external signals. Exposure is established before controls are applied or relied upon.
Map & Enforce Controls
Expected controls are automatically determined by the model, mapped to the site and cargo context, and scored for effectiveness. Verification scope is defined by risk — not discretion.
Verify Once. Trust Everywhere.
Evidence is captured through AI-directed verification, cryptographically sealed, and locked to place, time, and inventory. Proof cannot be reused, detached, or selectively applied.
Core Platform Modules
Sphere operates as a modular AI risk intelligence platform, designed to enforce trust by anchoring risk, verification, and evidence to physical reality through geospatial automation.
Each module operates on the same proof layer, ensuring consistency, auditability, and scale from day one.
Risk360
Risk360 anchors each storage site to its physical footprint using a geospatial risk matrix. It analyses inherent risk, determines expected controls, and computes a defensible residual risk rating.
This anchored risk baseline governs all verification through our Verify App, ensuring evidence is captured against the correct location, inventory context, risks, and controls — and remains consistent over time.
Verify
Verify is Sphere’s execution layer, enforcing AI-directed verification in the physical world.
It captures time-stamped, location-locked evidence directly against the Risk360 baseline. All evidence is cryptographically sealed and linked into Sphere’s Proof Graph, creating tamper-resistant verification that strengthens trust across the storage ecosystem.
EcoSphere
Baseline environmental and natural hazard exposure already feeds into Sphere’s residual risk calculations within Risk360.
EcoSphere extends this capability into a dedicated module, deepening climate and hazard intelligence using forward-looking scenarios and advanced analytics — built on the same geospatial and proof architecture.
This module will be introduced in a future release.