Built on Biology
Biotechnology is increasingly the engine that drives therapies for our deadliest diseases, nutrition to feed a growing global population, and energy & materials for a sustainable future.
Biological data are almost entirely unstructured
This makes biological data especially challenging to analyze, and most of the unstructured data is discarded.
Tools for Understanding and Predicting Biology
Immense quantities of routinely collected omic data are discarded simply because their unstructured content is so challenging to interpret
These discarded data contain untapped insights for data-backed decision making critical to:
Health & Longevity
Matterworks has built the first Large Spectral Model
An LLM-like semantic foundation for directly interpreting raw instrument data that offers an AI breakthrough for biology
Whole metabolome reading
Solving the mass spec holy-grail of absolute quantitative metabolomics
Global biological context
Search and sample comparisons using total-ome embeddings
API for fine-tuned prediction
Low code or no-code solutions for discovery, clinical, diagnostics, and process models