Discover
Define performance objectives, operating environments, and candidate systems based on customer requirements.
D2S combines AI agents, robotics, materials science, automated qualification, and manufacturing validation into a single autonomous engineering platform that transforms engineering concepts into production-ready technologies.
AI agents combine physics models, experimental evidence, performance objectives, and manufacturing constraints to identify materials with the strongest potential for technical and production success.
Every recommendation considers not only predicted performance, but also manufacturability, qualification, and practical pathways to scale.
AI agents generate plans that robotic workcells carry out autonomously. Materials are synthesized, processed, characterized, and mechanically tested while every result is captured as structured evidence.
Every experiment strengthens the evidence graph, reducing uncertainty and continuously improving future decisions.
Qualification is integrated from the beginning. Mechanical testing across different rates and temperatures, characterization, manufacturing feasibility, and scale-up assessment are all incorporated into the development workflow.
The result is greater confidence before production: lower technical risk, stronger qualification packages, and a faster path from discovery to manufacturing.
Every promising material must ultimately become a manufacturable product. D2S evaluates processing routes, solidification behavior, manufacturability, and production risks before major downstream investments are made.
By integrating manufacturing validation into the discovery process, customers gain production-ready evidence rather than isolated laboratory results.
Materials development is too often slow, disconnected, and risky. D2S closes the loop by integrating discovery, AI-guided design, autonomous experimentation, qualification, and manufacturing validation into a single continuous workflow—reducing technical risk before production decisions are made.
Define performance objectives, operating environments, and candidate systems based on customer requirements.
AI agents combine physics, experimental evidence, and manufacturing constraints to identify promising materials and practical pathways.
Autonomous robotic synthesize, process, characterize, and test materials while generating structured evidence.
Generate repeatable evidence for performance, manufacturability, reliability, and customer qualification.
Evaluate manufacturing feasibility, processing routes, and scale-up risks before committing to production.
D2S is advancing arc melting from a manually operated process into a repeatable, data-connected autonomous workflow.