Primary Metals Group
AI and IoT Solutions for Primary Metals
Primary Metals Group consists of AI and IoT portfolio companies serving industries that transform raw minerals and recycled materials into steel, aluminum, cast components, rolled products, engineered powders, and reusable metals. Across these operations, production depends on precise coordination of materials, equipment, workforce, and logistics rather than isolated manufacturing processes. AI and IoT systems help primary metals manufacturers identify and locate people, coils, billets, molds, tools, containers, scrap, and production assets throughout complex industrial facilities. AI can optimize material flow, improve production scheduling, reduce operational delays, strengthen traceability, and support safer execution of maintenance and manufacturing activities. IoT provides the connected identification infrastructure that enables real-time operational visibility across steel mills, foundries, rolling plants, powder metallurgy facilities, aluminum processing operations, and metal recycling yards, helping organizations improve productivity while maintaining quality and operational control.
Portfolio Companies under Primary Metals
Metalliq AI
Steel production involves a tightly connected sequence from raw-material handling and ironmaking through steelmaking, continuous casting, slab handling, reheating, rolling, and finished-coil storage. Metalliq AI can help steel producers maintain operational continuity across these stages by using AI to understand the location and movement of slabs, billets, coils, ladles, refractory materials, mobile equipment, and other production resources. Production teams can use this information to identify material waiting between processes, locate a specific heat or slab, and coordinate downstream operations when casting or rolling schedules change.
Turnaround and maintenance activities present another demanding application. Large steel plants may simultaneously manage contractors, cranes, tools, replacement components, refractory supplies, and work areas across multiple production units. Metalliq AI can help planners determine where critical resources are located and identify movement patterns that contribute to delays. AI-based analysis can also support coil-yard organization and dispatch preparation, helping reduce material searches and routing errors between finishing, storage, and shipment.
Alumetra AI
Aluminum and non-ferrous metal production requires careful coordination of alloy grades, billets, ingots, molds, extrusion tooling, fabricated products, and reusable handling equipment. Alumetra AI can help manufacturers manage these material flows from casting and homogenization through extrusion, rolling, finishing, storage, and shipment. AI can determine the location and processing status of specific metal lots, helping production personnel identify material awaiting the next operation and reducing unnecessary movement between processing and storage areas.
For extrusion and other forming operations, tooling availability can directly affect production schedules. Dies, fixtures, racks, containers, and other specialized resources frequently circulate between production lines, maintenance shops, and storage locations. Alumetra AI can help planners locate the tooling required for an upcoming production order and analyze historical movement to identify recurring preparation delays. For aluminum producers handling numerous alloy specifications and customer orders, these capabilities can improve material segregation, reduce changeover delays, and provide clearer visibility from cast product through finished shipment.
FoundryCast AI
Foundry operations are governed by a sequence of mold preparation, core production, melting, pouring, cooling, shakeout, finishing, machining, inspection, and shipment. FoundryCast AI can help manufacturers follow castings as they progress through these stages, particularly when multiple customer orders and casting configurations are being processed simultaneously. AI can identify which castings are awaiting finishing or inspection, locate work-in-progress within the facility, and highlight production orders that are accumulating delays between operations.
Tooling represents a particularly important application in foundries. Patterns, core boxes, molds, fixtures, and other reusable resources must be available when a casting campaign begins and may require maintenance or refurbishment between runs. FoundryCast AI can help production planners determine the availability and location of these resources before scheduling work. AI can also associate casting identifiers with their movement through shakeout, finishing, machining, and inspection, providing a more useful production history for investigating misplaced work, delayed orders, or quality-related events.
MetalProcess AI
Metal forming and rolling depend on precise sequencing because a delay involving one slab, billet, coil, roll, die, or changeover resource can affect an entire production schedule. MetalProcess AI can help rolling operations determine where material is positioned within the production sequence and whether it is ready for the next stage. In a coil-processing environment, AI can help coordinate movement between rolling stands, cooling, coiling, inspection, finishing, storage, and dispatch, making it easier for planners to identify coils that are waiting unexpectedly or have been routed incorrectly.
Changeover operations provide another practical application. Work rolls, backup rolls, mandrels, guides, dies, tooling, and lifting equipment must be prepared and positioned before a production change can occur. MetalProcess AI can help coordinate these resources with scheduled orders and identify preparation gaps before they affect mill availability. AI can also analyze coil movement across storage locations to improve dispatch sequencing and reduce unnecessary handling, particularly in high-volume mills where thousands of coils may occupy different storage and processing zones.
PowderForge AI
Powder metallurgy has a distinctive production flow in which metal powders are prepared and blended before being compacted, sintered, sized, finished, inspected, and packaged. PowderForge AI can help manufacturers establish a clear operational history for powder batches and the components produced from them. AI can identify where a batch or work order is positioned in the process, recognize material that has remained at an intermediate stage longer than expected, and help production personnel coordinate the transition between pressing, sintering, finishing, and inspection.
Precision tooling is equally important because powder presses depend on dies, punches, molds, and fixtures matched to specific component geometries and production requirements. PowderForge AI can help planners locate the correct tooling and determine whether it is available, undergoing maintenance, or assigned to another production run. For manufacturers producing small, complex, or high-value powder-metal components, AI-assisted traceability can connect powder lots with production orders and finished components, supporting investigation of material-routing discrepancies while providing stronger visibility across the manufacturing sequence.
MetalRen AI
Metal recycling and scrap processing operates very differently from conventional metals manufacturing because incoming material can arrive in mixed grades, irregular forms, bulk loads, bins, bales, and customer-specific shipments. MetalRen AI can help recycling facilities establish a more organized view of material as it moves through receiving, sorting, separation, processing, stockpiling, and outbound loading. AI can help operators determine where a particular scrap load or processed material is located, how long it has remained in a yard zone, and whether it has reached the appropriate processing stage.
Material segregation is especially important for valuable ferrous and non-ferrous grades. AI-assisted identification can help distinguish aluminum, copper, stainless steel, ferrous grades, specialty alloys, and other recovered materials according to their assigned storage or processing locations. The same operational information can support outbound order preparation by helping personnel locate the required grade and quantity before loading. For large recycling yards, AI can also reveal recurring congestion and inefficient material movement, helping operators make better use of available storage areas and reduce unnecessary handling of recovered metals.
Building the Future of Industrial AI and IoT for Primary Metals
For more than three decades, GAO Group of Companies has invested heavily in R & D of industrial IoT. Since generative AI was proven useful in industrial applications, we have been developing AI and IoT technologies, and we have founded Aperture Venture Studio to build, launch, and scale next-generation AI and IoT companies for various industries.
Aperture has been able to attract top AI and IoT technical experts, entrepreneurial and operational executives, influential investors and industry leaders as corporate partners.
Furthermore, we have developed a successful TekSummit and Aperture Ventures Summit to discuss advanced topics on AI and IoT.
As a result, we have built diversified ecosystems and vibrant technical communities for AI and IoT.
To address the enormous and fast-rising demands of AI and IoT in Primary Metals, we have created Aperture Venture Studio.
Join Aperture Venture Studio
We welcome:
- Advisors, co-founders, founding members and prospective employees
- Strategic, venture, angel, and institutional investors
Let’s work together to build the future of AI and IoT for Primary Metals.