Supplier Intelligence
Understands supplier capabilities, certifications, capacity, ESG maturity and risk signals.
AI for the planet
AI for Sustainable Manufacturing.
How AAGM’s MaterialsIQ platform uses AI to reduce waste, improve clean-tech manufacturing yield, trace Scope 3 emissions and strengthen climate-resilient supply chains.
The Planetary Problem
The energy transition depends on scaling clean-tech manufacturing faster — especially solar, batteries, semiconductors and advanced materials. Yet the manufacturing systems behind this transition remain fragmented, document-heavy and carbon-blind. Critical decisions about suppliers, materials, quality, traceability and ESG impact are still made with incomplete data.
Why AI Is Needed
Manufacturers now need to optimize across cost, quality, yield, availability, supplier risk, embedded carbon, ESG compliance and climate resilience simultaneously. Traditional ERP, procurement and quality systems were not designed for this level of multi-variable reasoning. MaterialsIQ uses AI to connect fragmented data and convert it into actionable manufacturing intelligence.
What MaterialsIQ Does
Five intelligence capabilities, one platform.
Material Intelligence
Connects material specifications, batches, quality outcomes and production performance.
Sustainability Intelligence
Tracks Scope 3, provenance, carbon signals, ESG documentation and compliance evidence.
Yield Intelligence
Identifies material-process-performance patterns that drive scrap, rework and production loss.
Agentic Copilot
Enables procurement, quality, ESG and operations teams to ask questions, investigate issues and act faster.
AI Architecture
Fragmented inputs in. Decisions out.
Data Inputs
01- Supplier documents
- Material specs
- Quality records
- Production data
- ESG documents
- Logistics data
- Certifications
- External risk signals
MaterialsIQ Intelligence Layer
02- Knowledge graph
- AI agents
- Material-process-performance models
- Federated learning
- Digital material passports
- Recommendation engines
Outputs
03- Supplier recommendations
- Lower-carbon alternatives
- Yield insights
- Risk alerts
- ESG evidence
- Traceability
- Executive intelligence
Google AI Integration Roadmap
A model-flexible AI platform.
MaterialsIQ is designed as a model-flexible AI platform. As part of future AI ecosystem development, AAGM can explore integrating Google AI technologies across three areas:
Gemini for manufacturing copilots
Power MatiE, our AI copilot, for natural-language reasoning across procurement, quality, ESG and supplier intelligence.
Gemma for private, domain-tuned models
Deploy lightweight, controlled models for supplier document intelligence, material classification and ESG evidence extraction.
Geospatial AI for climate-aware supply chains
Enrich supplier and logistics risk scoring with location-level environmental and climate-risk signals.
Exploratory roadmap only. No partnership, affiliation or endorsement is implied. All product names are trademarks of their respective owners.
Current Focus Areas
Solar Manufacturing
Improve module yield, reduce material waste and trace supplier/material provenance.
Battery Manufacturing
Reduce scrap, qualify resilient suppliers and support sustainable energy-storage scale-up.
Semiconductor Manufacturing
Improve visibility across specialty materials, gases, chemicals, supplier risk and Scope 3 data.
Impact Objectives
Our impact objectives are to help manufacturers reduce scrap, improve clean-tech output, increase traceability, strengthen Scope 3 visibility, qualify sustainable suppliers faster and build more resilient supply chains.
Building the Intelligence Layer for the Clean-Tech Manufacturing Economy
AAGM’s long-term vision is to enable every manufacturing decision to balance cost, performance, resilience and planetary impact.