Agent Hierarchy
Integrate first, abstract second, replace selectively. The Trading CRM remains the system of record; AgentOS turns the CRM and surrounding systems into a coordinated, explainable intelligence layer.
Research, buyer–supplier matching, follow-up, analysis, documentation, and cross-system coordination are compressed and made traceable by specialist agents.
Relationships, consequential decisions, approvals, and the final buyer/supplier conversations remain with people. Agents prepare; humans decide.
The Trading CRM, cieTrade, Zoho, accounting, email, telephony, documents, and freight services feed the model. AgentOS turns them into one explainable layer — no live connections in this demo.
- 1Connect and normalizeConnect and normalize priority operating data from the Trading CRM and surrounding systems — companies, sites, contacts, materials, opportunities, loads, activity.
- 2Establish the knowledge graphBuild the company knowledge graph and shared commercial definitions — grades, pricing basis, margin policy, freight lanes.
- 3Assist research and coordinationAssist research, qualification, matching, follow-up, and documentation — agents accelerate the work humans already do.
- 4Orchestrate with human checkpointsOrchestrate cross-system workflows with human checkpoints — every consequential decision stops at a person.
- 5Measure and selectively automateMeasure outcomes and selectively automate low-risk actions only after the boundary is approved.
- 6Continuously improveContinuously improve from decisions, exceptions, and operating feedback.
| Workstream | Dependencies | Governance | Measurable outcomes |
|---|---|---|---|
| Data foundation | CRM schema + access | Data ownership, definitions | Canonical companies/contacts/opportunities/loads; grade & pricing basis agreed |
| Knowledge graph | Data foundation | Evidence & policy review | Shared commercial definitions; margin & route knowledge traceable |
| Assisted workflows | Knowledge graph | Human approval checkpoints | Qualification, matching, follow-up, documentation assisted with review |
| Measurement | Assisted workflows | Monthly leadership review | Load counts, cycle times, margin protection, follow-up coverage measured |
What AgentOS demonstrates, step by step. This is a simulated, illustrative operating model — not a claim about how Abir operates today.
A commercial request is decomposed into accountable work items with owners, dependencies, and review states.
See it live →Agents act inside defined autonomy boundaries; human authority stays explicit for consequential actions.
See it live →Every recommendation is linked to the records, SOPs, sources, and runs that support it.
See it live →Freight, landed cost, margin, and risk recompute through one financial model across every surface.
See it live →The system prepares the recommendation; leadership approves, requests changes, or rejects.
See it live →One decision updates opportunity state, work, communications, economics, and the briefing — traceably.
See it live →Throughput, bottlenecks, margin, and risk inform how the operating model evolves.
See it live →