We are designing for biological assembly from the ground up.

The Problem

Current Manufacturing Was Not Designed for This

Existing fiber manufacturing technologies were built for cellulose and synthetic polymers. They treat the process as a black box: input a feedstock, output a fiber, with little tunability and no predictable way to program performance outcomes. When researchers try to use these systems for protein-based materials, the conditions required for hierarchical self-assembly simply cannot be met.

Scaling compounds the problem. Conventional manufacturing scales up by increasing volume, which changes the underlying biophysics and alters the product entirely. A fiber that works at the bench fails at the pilot line, not because the chemistry is wrong but because the manufacturing regime has shifted underneath it.

Meanwhile, recent advances in computational materials discovery have focused almost entirely on hard and crystalline matter, because we have well-established simulators for those systems. Soft matter, the domain of proteins and biological composites, has no equivalent emulator. The data infrastructure is missing. We are building it alongside the manufacturing.

Our Approach

Assembly-First Manufacturing

Rather than adapting legacy fiber processes to accommodate proteins, we have designed a manufacturing system around the physics of biomaterial assembly. We leverage novel phase-change triggers for protein self-assembly to create predictable, programmable performance outcomes from the start.

Advances in micro- and nanofluidics allow us to automate dope creation and characterization with high precision. We combine this with spinning techniques that preserve the biophysics across scale: contact pulling, electrospinning, and microfluidic spinning. Because these processes scale out in parallel units rather than scaling up in volume, the conditions at each production point remain identical. Lab and factory converge.

Automation and robotics give us repeatable, normalized processes that feed both standardized characterization and digital twin development. Rapidly accelerating capabilities in protein design and production mean that engineered proteins are now reliable, tunable feedstocks rather than exotic research materials.

The result is a manufacturing platform where material outcomes are predicted and programmed, not discovered through trial and error.

What It Enables

From Predictable Composites to Programmable Systems

At the first level, our platform produces composite materials with predictable cost and performance characteristics. We generate techno-economic analyses for every input combination, providing clear evidence for resource allocation across target applications in aerospace, biomedical devices, robotics, and remote or distributed manufacturing.

At the next level, control over multi-scale assembly enables materials with spatial gradients: fibers whose properties vary along their length or cross-section. This opens applications in vibration damping, increased force and shear tolerance at material junctions, reduced fracture at interfaces between dissimilar materials, and new degrees of freedom for robotic dexterity, artificial tendons, and artificial muscles.

At the frontier, nanoscale material design and rapid assembly create pathways to fibers with optical, electrical, and computational function. Fibers tuned to match the mechanical characteristics of biological tissue while enabling electrical conduction from the nervous system to a computer interface. Composites that don't just carry load but carry information.