Layer 04 · Capital
Financing Layer
Trade finance, invoice discounting and ESG-linked credit underwritten on live production data.
AI agentsFederated learningBlockchainSupplier graph
Manufacturing OS
Accelerating Manufacturing Excellence through Data, AI & Material Intelligence.
The Manufacturing Intelligence Operating System for the global clean-tech economy — unifying suppliers, materials, transactions and financing on one AI-native platform.
Federated learning · privacy-preserving
Research partners: NTU · SERIS
Suppliers
12,480 verified
Manufacturers
GW-scale
Yield uplift
+3.7pp
CO₂e tracked
2.1Mt
The Problem
Manufacturing is too slow, too fragmented, too analog.
The energy transition demands gigawatts of clean-tech output — built on supply chains that still run on PDFs, lab tickets, and tribal knowledge.
No supplier visibility
Procurement teams operate on stale spreadsheets and broker relationships — without lot-level traceability.
Data silos
MES, LIMS, ERP, and supplier data never converge. Engineers can't correlate incoming material with outgoing yield.
Slow yield optimization
It takes quarters of trial-and-error to dial in a new recipe. Competitors at GW scale move faster than you can iterate.
ESG complexity
Scope 3 disclosures, CBAM, SBTi — all manual, all error-prone, none integrated with the procurement reality.
MaterialsIQ Platform
A layered intelligence architecture.
Four stacked layers — from raw signal to financed transaction — powered by AI agents, federated learning, blockchain provenance and a verified supplier graph.
Layer 03 · Commerce
Transactions Layer
Verified procurement, sales orders, digital passports and blockchain-anchored provenance.
AI agentsFederated learningBlockchainSupplier graph
Layer 02 · AI
Intelligence Layer
AI agents, federated learning models and recommendation engines for yield, sourcing & ESG.
AI agentsFederated learningBlockchain
Layer 01 · Foundation
Data Layer
Unified MES, LIMS, ERP, supplier and lot-level material data streamed into one ledger.
AI agentsFederated learning
Proof in the Field
Case Studies — Margin Recovered Through Material Intelligence
Real factory incidents where AAGM turned hidden material and process variability into measurable financial gain.
Case 01 / 03
Solar Module Manufacturing
$480KAnnual yield loss averted
Hidden Micro-Cracks Cost a Line $480K — AI Recovered It in One Batch
10
Modules saved per batch
62%
Defect rate reduction
<24h
Time to root cause
Problem
AOI cameras silently missed micro-cracks at the pre-EL stage. Defective modules slipped through to post-EL inspection — burning labor, energy and material on every flawed unit before scrap.
AI Insight
AAGM correlated incoming film batch fingerprints (embossing pattern, glossiness, orientation) with downstream camera visibility. The platform flagged the offending batch signature before it hit the line.
Resolution
Immediate orientation flip restored AOI visibility; long-term embossing redesign eliminated the failure mode. Result: zero scrapped modules from this defect class and ~$480K/yr recovered margin.
Competitive advantage
A moat that compounds with every transaction.
Other platforms manage suppliers. AAGM understands why performance varies — and turns that understanding into a defensible data network.
AI + Federated Learning
Train across customer datasets without moving raw data — each manufacturer benefits from collective intelligence while keeping IP private.
Blockchain traceability
Anchored material provenance and transaction records — immutable audit trail for CBAM, SBTi, and customer disclosures.
Proprietary dataset
Material-process-performance models built with NTU & SERIS. The only dataset linking lab-grade material properties to GW-scale production yield.
Network effects
Every transaction strengthens the supplier graph. Every onboarded line refines the AI. Switching cost compounds with every datapoint.
Research Partners
Backed by world-class research institutions.
NTU Singapore
Nanyang Technological University
Leading research in materials science, AI, and clean-energy systems.
SERIS
Solar Energy Research Institute of Singapore
World-class solar R&D and PV materials characterization.
UNSW
University of New South Wales
Pioneering photovoltaics and sustainable manufacturing research.
Get started
Build the future of Manufacturing Intelligence.
Join the operators, suppliers and partners building the operating system for the global clean-tech economy.