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Company overview

The agentic operating system for the mid-market supply chain

SCMX moves enterprises from reactive firefighting to autonomous orchestration. A mesh of collaborative AI agents senses disruptions, simulates their network-wide impact, optimizes the fix with real solvers, and — within guardrails and human approval — helps execute the resolution and measure the savings it delivers.

Mid-market
$50M–$1B enterprises
18
Verticals modeled
~$53B
Agentic-SCM market by 2030 (Gartner)
Live
Production control tower

A category is forming — and the mid-market has been left out

Enterprise supply chains are entering their agentic era. As organizations move from AI pilots to systems that act rather than merely advise, Gartner projects the market for agentic AI in supply chain to reach roughly $53 billion by 2030. Yet the platforms driving that shift were built for the Fortune 500 — heavy, seat-priced, and measured in multi-year deployments. The mid-market — manufacturers, wholesale distributors and retail & CPG companies between $50M and $1B in revenue — is big enough to feel every stockout, late supplier and recall, but too lean to absorb an 18-month enterprise rollout.

SCMX was built to close that gap: an agent-first operating system that delivers the breadth incumbents charge a fortune for, assembled into a single platform that reaches value in days.

A closed loop, not another dashboard

Most tools tell you what happened. SCMX runs a continuous loop that catches problems earlier and acts on them faster. A supervisor-orchestrated mesh of specialized agents — demand, inventory, supplier, logistics, production and compliance — senses the signals that precede disruption. A supply-chain knowledge graph simulates how each risk propagates across the network. Real optimization solvers compute the lowest-cost fix under the customer's own policies and constraints. And on human approval, agents help execute the resolution under deterministic guardrails.

Crucially, the loop closes on measured outcomes. When an action lands, SCMX compares what actually happened against a baseline frozen at decision time and writes the realized savings to an auditable outcome ledger — savings that are measured, not estimated.

Intelligence that compounds, governance that reassures

Every measured outcome feeds a decision-intelligence model that retrains itself as the ledger grows — so recommendations sharpen the more a customer runs, while execution stays firmly human-approved. Before any of it begins, SCMX scores the quality of a customer's master data and surfaces the fixes up front, because most supply-chain deployments stall on dirty data.

Governance is part of the product, not an afterthought. Guardrails, approvals, role-based access, database-per-tenant isolation and an immutable audit trail sit directly in the execution path — built for the enterprises that want AI that recommends and humans who decide.

Aligned on outcomes

SCMX prices on results: a base platform fee plus an optional success fee on the savings customers actually realize. The company is founder-led and currently in design-partner pilots, with a live production control tower that prospects can explore today on representative data before connecting their own ERP, EDI or POS feeds.

“The next decade of supply chain won't be won by dashboards. It will be won by systems that sense, decide and act — and that can prove, in dollars, that they were right. We're building that system for the companies the giants overlook.”
— The SCMX team
How it works

Sense → simulate → optimize → execute

01

Sense

Specialized agents watch demand, inventory, suppliers, logistics and production for the signals that precede a disruption.

02

Simulate

A knowledge graph propagates each risk across the network — blast radius, single points of failure, revenue at risk.

03

Optimize

Real solvers compute the lowest-cost fix under your policies and constraints.

04

Execute

On approval, agents act within guardrails, then measure realized savings against the decision baseline.

What sets it apart

Real decision intelligence, governed end to end

Self-optimizing decision intelligence

A decision-intelligence model that learns from measured outcomes and retrains itself as they accrue — recommendations sharpen the more you run, while execution stays human-approved.

Closed-loop execution with measured ROI

On approval, agents issue the purchase order under deterministic guardrails, then measure realized savings against a decision-time baseline and write them to an auditable outcome ledger.

Data readiness, up front

Master-data quality is scored on day one — duplicate SKUs, phantom stock, missing costs, mismatched units — and the fixes are surfaced before the agents ever run.

Real decision optimization

Google OR-Tools solvers compute reorder quantities, safety stock, inventory rebalancing and carrier selection — decisions grounded in math, not just dashboards.

Knowledge graph (GraphRAG)

Cross-entity reasoning over the supplier → product → warehouse → customer graph for blast-radius and single-point-of-failure analysis.

Governance-native by design

Guardrails, approvals, RBAC, tenant isolation and an immutable audit trail are part of the execution path — not features bolted on afterward.

Why it matters

Value for operators, buyers and investors

For supply-chain leaders

From firefighting to foresight

  • Catch disruptions days before they hit the P&L, with a fix already drafted.
  • Right-size inventory to free working capital without new stockouts.
  • Keep humans in control — nothing high-impact happens without an approval.
  • Reach value in days on your own ERP, EDI or POS feed, not an 18-month rollout.
For acquirers & strategic buyers

A modern, agent-first stack

  • Built as an orchestration platform from the ground up — not AI grafted onto legacy planning.
  • Enterprise controls in place: SSO, RBAC, per-tenant isolation, SOC 2-ready evidence.
  • Reaches the underserved mid-market that heavyweight suites price out.
  • Coverage across 18 verticals with installable, tunable playbooks.
For investors

A compounding data asset

  • Positioned in agentic AI for supply chain — a category Gartner projects to reach ~$53B by 2030.
  • A proprietary decision → outcome dataset that grows with every guardrailed action.
  • Incentive-aligned pricing: revenue tied to the savings customers actually realize.
  • Governance as a moat, for the enterprises that require AI that recommends and humans who decide.
At a glance

Company fact sheet

Category
Agentic supply-chain operating system
Segment
Mid-market enterprises ($50M–$1B revenue)
Operating model
Sense → simulate → optimize → execute, under human approval
Commercial model
Outcome-based — platform fee plus a success fee on realized savings
Deployment
Cloud (AWS), database-per-tenant isolation
Security
SSO (OIDC/SAML), RBAC, encryption at rest, SOC 2-ready, immutable audit log
Coverage
18 industry verticals modeled, with installable playbooks
Stage
Founder-led · pre-revenue · in design-partner pilots
Availability
Live production control tower, explorable today on representative data

SCMX is in design-partner pilots; measured-outcome figures reflect the platform's methodology on representative data and are validated with customers during pilots.

About SCMX

SCMX is the agentic supply chain operating system for the mid-market. It combines a mesh of specialized AI agents, real optimization solvers, a supply-chain knowledge graph and a self-optimizing decision-intelligence model to sense disruptions, simulate their impact, optimize the fix and — under human approval — help execute it and measure the savings. Built governance-native, with SSO, role-based access, per-tenant isolation and an auditable outcome ledger, SCMX is modeled for 18 industry verticals and priced on the results it delivers. The company is founder-led and in design-partner pilots.

Agent-first Governance-native Outcome-based 18 verticals

Media contact

For interviews, briefings, product demonstrations or additional materials, please reach out. We respond to press inquiries promptly.

press@scmx.ai

See the platform for yourself

Explore the live control tower on representative data, or talk to us about a design-partner pilot on your own ERP, EDI or POS feed.