PRICING

Fast single-sequence protein structure prediction.

Input: amino acid sequence → Output: PDB structure + pLDDT confidence score

Protein language model embeddings for ML pipelines.

Input: amino acid sequence → Output: 1280-dimensional embedding vector

De novo protein sequence design from backbone structure.

Input: PDB structure → Output: designed sequences + recovery scores

Biomolecular complex structure prediction at AF3 quality.

Input: protein sequences → Output: complex PDB + confidence scores

Molecular embeddings and property prediction from SMILES.

Input: SMILES string → Output: embeddings + molecular properties

Molecular properties, fingerprints, and similarity.

Input: SMILES string → Output: properties + Morgan fingerprint + similarity score

Natural language descriptions of molecules from SMILES.

Input: SMILES string + task → Output: text description or IUPAC name

Molecular docking via diffusion model.

Input: protein PDB + ligand SMILES → Output: binding poses + affinity scores

Universal ML force field — energy and forces for any material.

Input: atomic structure → Output: energy (eV) + forces (eV/Å)

Equivariant neural network interatomic potential.

Input: atomic structure + cutoff → Output: energy (eV) + forces (eV/Å)

Deep potential molecular dynamics force field.

Input: atomic structure + box → Output: energy + forces + virial tensor