One AI workflow, six component groups
From intake to action, memory to guardrails — AI takes the repetitive work, people keep judgment and release. Every component here runs in production, not on a slide.
① Sense · Intake
Turn business scattered across email, PDF and IM into structured data.
Document AI intake
One inbox for email / PDF / IM; AI extracts structured trade drafts — every field preserved, amounts at commodity precision.
Market intelligence terminal
Multi-source market data and fundamentals, auto-collected — futures, physical and macro on one screen, all real and traceable.
② Understand · Explain
Not just the number — why it happened and what it affects.
AI explanation cards
Four-part readings of anomalies: what / why / impact / suggestion — numbers come from fact slots, never paraphrased by the model.
Anomaly detection center
Document gaps, credit breaches, P&L flips — detected and surfaced proactively, not found in month-end reports.
③ Act · Collaborate
An AI employee drafts; a person releases — not a black-box autopilot.
AI action drafts
Tiered execution: light actions suggested, heavy actions drafted only — human approval required, four layers of defense.
Task center
Anomalies become tasks automatically, overdue ones escalate — who owns what, visible end to end.
AI morning brief
Before the market opens: the exposures, anomalies and moves you should look at, on one page.
④ Memory · Learning
Conventions accumulate trade by trade — it learns your business.
Business memory
AI remembers your conventions and preferences — visible, deletable, switchable, with expiry. The memory is yours, not the model's.
Glossary + feedback loop
Terms defined before use; every human correction feeds the next answer.
⑤ Guardrails · Governance
Helps, never meddles — AI has no write access by architecture, not by promise. Where money is involved, that's the floor.
Number-fidelity defenses
Critical numbers are never generated by the LLM: slot-fed values, validation gates, temperature 0, source attribution — multiple layers.
Tool safety gate
AI holds read-only tools and never writes business data; every call is logged and auditable.
Evaluation layer
Model output is continuously evaluated; upgrades pass the eval set before going live.
⑥ Foundation · Private
Data stays in-house. Models stay swappable.
Private deploy + local models
Local LLM + RAG — private data never leaves your environment; runs on one machine, even offline.
Model registry
Models managed explicitly and hot-swappable — no vendor lock-in. When a better model ships, switch to it.
First full deployment: xRubber CTRM
The complete rubber trade — contracts, inventory, matching, reconciliation and risk — all of the components above, composed in production.
Not in rubber? Tailor it to your commodity →