AI Design and Discovery

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-guided materials design and discovery visualization

Autonomous Make, Test, Learn

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.

Autonomous materials make, test, and learn workflow

Qualification Built Into Discovery

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.

Advanced materials qualification and testing workflow

Manufacturing Validation & Scale-Up

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.

Manufacturing validation and materials scale-up workflow

One platform. All five pieces.

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.

Discover

Define performance objectives, operating environments, and candidate systems based on customer requirements.

Design

AI agents combine physics, experimental evidence, and manufacturing constraints to identify promising materials and practical pathways.

Make & Test

Autonomous robotic synthesize, process, characterize, and test materials while generating structured evidence.

Qualify

Generate repeatable evidence for performance, manufacturability, reliability, and customer qualification.

Scale

Evaluate manufacturing feasibility, processing routes, and scale-up risks before committing to production.

Progress in Autonomous Arc Melting

D2S is advancing arc melting from a manually operated process into a repeatable, data-connected autonomous workflow.

Progress of the autonomous arc-melting system and workflow

Built, protected, and ready to scale.

$50M+ U.S. Government contract base validating mission-critical demand.
Operational Autonomous arc-melting and materials testing workflows already in use.
Protected IP Patent and software protection around autonomous synthesis and testing systems.
Scale Next Replicate proven systems, expand manufacturing and testing modalities, and integrate workflows.