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AI-native · Rubber first · Multi-commodity

The AI-native
OS for commodity trading

Let AI read documents, post trades, watch exposure and control risk. Starting with the rubber trade, expanding across commodities — and becoming an enterprise AI operating system that spans ERP-class workflows.

Book a demo →See how it works
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Capabilities

Hand the busywork of commodity trading to AI

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Intake to books

Trades buried in email, PDF and IM — AI extracts them into structured fields; a human confirms in one click. No more re-keying.

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Exposure & MtM

Every trade updates net long/short exposure and mark-to-market P&L, live with the market — risk visible now, not at month-end.

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Risk & compliance

Credit, margin and fulfillment limits are built in as gates; breaches auto-hold, warn and log — no one has to watch them.

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Audit trail

Every AI suggestion and human decision is logged — replayable, explainable, and ready for audit.

Product

xRubber CTRM

The first product on the xvalos platform: an AI-native CTRM for the natural & synthetic rubber trade — contracts, inventory, matching, reconciliation and risk on one pipeline, built on a commodity-agnostic model that extends across commodities.

Document intake · human review required Exposure / MtM / credit, live Private deployment · data stays in-house
Explore xRubber CTRM →

How it works

An AI employee — humans decide

01

Connect

Hook up your mailbox, IM, documents and market feeds — AI takes its place in your existing workflow.

02

Collaborate

AI drafts, extracts and warns; people judge and release — an AI employee, not a black-box autopilot.

03

Compound

Conventions, memory and audit build up trade by trade — it learns your business and gets faster the more you use it.

Roadmap

Specific to general, one throughline

Go deepest on the rubber trade first, then reuse the commodity-agnostic foundation for bigger scopes.

Now

Rubber CTRM

The full natural / synthetic rubber trade: contracts, inventory, matching, reconciliation, risk.

In progress

Multi-commodity

A commodity-agnostic model — adding a commodity means configuring data, not changing code. Metals, chemicals and softs to follow.

Long term

AI enterprise OS

Abstracted from CTRM into a general trading / fulfillment / finance core spanning ERP-class workflows.

Private deployment, data stays in-house

Local model + RAG keeps private data on-premises; money is decimal-precise throughout, the audit trail is complete, and it runs on a single machine, even offline.

Private deploy Local LLM Audit trail RBAC / SoD PITR backup License control

Let AI take over the repetitive work

Start with rubber — catch the mis-keyed trade, the breached limit, the runaway exposure before it books.

Book a demo →