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2 minute read
What private AI does once it is inside your CTRM
Most of the debate about AI in commodity trading has been about where it runs. That is the right place to start. Send your contracts, positions and P&L to an external model, and you hand your commercial edge to infrastructure you do not control. Euclid AI runs locally or inside a private environment, connected directly to the CTRM, so that data never leaves your perimeter.
That argument is largely settled. The more useful question now is what the intelligence does once it is inside.
Document entry provides the first visible impact
Document entry is the visible starting point. Contracts, invoices and confirmations arrive in dozens of formats and processing them by hand is slow and prone to error. Euclid AI reads them with 99.3% OCR accuracy across 50+ document formats, including handwritten contracts, and cuts typing time by 98%.
This is real operational value, and it is the part that firms notice on day one. It is also only where the work begins.
The operational core
Once the model is inside the environment and connected to the CTRM, the same intelligence applies across the data that drives the business, from P&L and risk to position-keeping and the reporting that compliance and management rely on. Because processing occurs within the perimeter, sensitive numbers never travel to an external API for processing. Auditability comes built in. Every automated step is traceable. This matters when a regulator or a counterparty asks how a figure was produced.
These are the workflows that span Euclid's five domains: Trading, Risk, Operations, Finance and Management. Document entry touches one of them. The intelligence layer touches all five.
Market data comes in, proprietary data stays put
Trading decisions need external context: prices, market data and third-party feeds. Private AI lets a firm bring in that data and run it against internal positions, without the reverse ever happening. Your contracts, counterparties and commercial logic do not leave to meet the data. The data comes to them.
This is also where a firm's own history becomes an asset. Euclid AI is trained on 15+ years of proprietary commodity trading data, and inside a private deployment, it can work with the institutional knowledge that usually sits unused across spreadsheets, past deals and email threads.
The architecture is the point
None of this is rare on its own. Plenty of tools read documents. Plenty of platforms run analytics. The difference is that Euclid does it on data that never leaves the client's control. That sovereign architecture is what makes it safe to point AI at the most sensitive information a trading firm holds. Without it, that information could not go near an external model. With it, the model comes to the data, and the data stays home.
That is the shift worth holding onto. Sovereign architecture and private AI enable a firm to put its most valuable data to work and retain every advantage it represents. Smart, sovereign CTRM, with the intelligence built into the operations it runs.
