NATURE TOOK MILLIONS OF YEARS.
OUR AI DOES IT IN DAYS.
We are engineering the end of permanent waste. Not through recycling, but through molecular evolution at silicon speed.
91% OF PLASTIC
IS NEVER RECYCLED.
The current system is broken. It was built for a world that didn't understand finite limits. We're not building a better bin; we're building better molecules.
Average decomposition lag
Annual ocean inflow
CARBON
WASTE
[ RAW_POLYMER_STOCKS ]
BIO-
POLYMER
[ ASSET_TYPE: BIO_ASSIMILATIVE ]
BIOSYNTHESIZE
THE ENGINE.
Traditional material science is a decade-long guessing game. The plan: use transformer-based models to simulate vast molecular search spaces in weeks, not years — and find the ‘Goldilocks’ polymer computationally first.
TARGETING
Defining mechanical loads and environmental triggers.
SIMULATION
Generative AI scans chemical space for degradation paths.
VALIDATION
Stress-testing digital twins in hyper-realistic sandboxes.
SYNTHESIS
Top candidates handed off to lab partners for real-world testing.
WE ARE RACING
THE CLOCK.
One person.
One problem worth solving.
This is an early-stage research project exploring whether AI can meaningfully accelerate the discovery of biodegradable plastic alternatives.
The approach is straightforward: use machine learning to search chemical space faster than traditional lab work allows, identify promising polymer candidates, and validate them through simulation before any synthesis happens.
No lab. No team yet. Just a clear hypothesis and the tools to test it.
AI-First
Machine learning drives every hypothesis.
Research Stage
Early-stage exploration of the problem space.
Open Mission
Solving a planetary problem, not a niche one.