Largescale Manufacturing intelligent materials and structures
Opti-Meta-Mech Framework:
Our AI-driven optimization framework tailors mechanical metamaterial architectures providing right fit for the applications—modulating internal geomtrical parameters—to eliminate stress concentrations and homogenize mechanical behavior. By encoding each design into our platform, we deliver bespoke polymer, metal, and ceramic solutions in hours, not days. Calibrated to your application, material system, and target properties, it achieves precise mechanical performance a
Hybrid-Bio-Inspired Modeling: Redefining Mechanical Trade-Offs
Leveraging bio-inspired hierarchical architectures, we balance strength–ductility and stiffness–toughness trade-offs via tailored soft–hard interfaces. Built entirely from constant-mean-curvature surfaces, our metamaterials deliver robust, fracture-resistant, ductile performance in ultralight components—from VR headsets and EV casings to aerospace wings—enabling bespoke mechanical profiles at any scale.
Smoothening mechanisms of advanced Microlevel Interfaces
Seamless Integration, Elevated Performance—All Without Added Time or Cost
At the core of our “O.M.M” technology is a geometry-driven interface design at microlevel that seamlessly locks together polymers, metals, and ceramics without adhesives or extra processing. These geomtrical optimiations on lattice levels deliver unrivaled interfacial strength, enhanced load-bearing capacity, and superior fracture toughness—all fully compatible with existing 3D-printing workflows.
Developing Nano-Alloy embedded Metamaterials
Nano-Alloy embedded Carbon Metamaterial
Nano‑alloy embedded carbon metamaterials are architected hybrids in which bimetallic/multimetallic nanoparticles are immobilized within engineered carbon scaffolds (e.g., graphene, CNT networks, porous carbons) to tailor effective permittivity/permeability and multi‑scale loss pathways. Composition‑ and size‑dependent electronic (and, where relevant, magnetic) responses of the nano‑alloys, coupled with the high‑conductivity, low‑density carbon framework,
Advancing Wearable Electronics with O.M.M technology
End-to-End AI-Driven FDM Workflow for High-Performance Applications:
Our AI-driven FDM workflow takes place(For Example: VR headset casing)from a precise CAD model through seamless structural optimization—wrapping it in a constant-mean-curvature mesh, running SwiftComp composite analysis, tuning geometry with a physics-informed Bayesian neural network, and automatically sizing for real-world loads—before producing a robust, lightweight part on an industrial FDM printer, all in one integrated pipe
Developing Advanced Orthopedic Impalnts with MIM
AI-Driven MIM Workflow for Ultra-Precision Orthopedic Implants
From detailed CAD modeling through CMC mesh integration, SwiftComp structural-genome analysis, physics-informed Bayesian neural-network optimization, and dynamic load-case sizing, this end-to-end pipeline culminates in high-resolution stereolithography printing—delivering flawlessly smooth, dimensionally accurate prototypes in a single, seamless process.
Developing Advanced Aerospace Applications with SLA
AI-Driven SLA Workflow for High-Fidelity Airfoil Prototyping
From a precise CAD model of your airplane wing through an optimized constant-mean-curvature surface mesh, SwiftComp structural-genome analysis, physics-informed Bayesian neural-network refinement, and automated boundary-condition sizing, this seamless pipeline delivers a flawless wing prototype via high-resolution stereolithography—complete and ready for aerodynamic testing
Developing Advanced Automobile parts with SLS
AI-Optimized SLS Workflow for Scalable EV Battery Casings
Starting with a detailed CAD design of the battery housing, this integrated process wraps it in a tailored CMC mesh, runs composite homogenization in SwiftComp, tunes geometry with a physics-informed Bayesian network, applies real-world loading profiles and dynamic sizing, and finishes in batch on an industrial SLS machine—producing heat-resistant, lightweight casings at production scale.