We help you collect large, context-rich datasets (binding, solubility, stability, expression) and feed them into AI to accurately predict and design novel proteins.
Models trained on sparse or out-of-context biology miss what matters: folding, degradation, and functional performance in real conditions. Relying on predictions alone leaves value in underexplored sequence space.
Pair design with massive, standardized data collection: generate sequence diversity, run high-throughput functional screens, validate in cell-free systems, and continuously feed results back into AI models.
High yield expression and rapid prototyping for enzymes and binders.
VHs/VHHs/nanobodies with validated binding correlation to HEK-expressed proteins.
Antibody formats with efficient assembly and QC by gel/binding assays.
Pichia-based extracts for eukaryotic folding and PTM-compatible synthesis.
HEK extracts for closer-to-native folding and validation.
Targeted diversification in host for efficient local exploration of sequence space.
Generate vast, targeted sequence diversity efficiently to explore neighborhoods around promising scaffolds without prohibitive synthesis costs.
Display-based and biochemical assays produce rich functional readouts at scale, suitable for supervised learning.
Rapid, small-scale expression in bacterial, yeast, and mammalian cell-free systems to measure folding, solubility, and activity before fermentation.
Clean schemas, QC, and metadata (buffers, temps, salts) make datasets plug-and-play for model training.
Iterative retraining with active learning prioritizes experiments that maximize information gain.
From bench-scale validation to fermentation with minimal re-engineering.
Full datasets and methods available upon request.
Rapidly explore sequence neighborhoods and prioritize designs likely to express and function.
Close the loop between design and experiment with standardized, AI-ready datasets.
De-risk scale-up by validating in cell-free systems before fermentation and downstream work.
Have a target or need rapid exploration around a scaffold? Let's talk.