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Platform

One loop: design, make, measure, learn.

A peptide is only as good as the data behind it.

We do not take quality on trust. Partners make each batch, an independent laboratory measures it, and every result is recorded as structured data. That record is what our models are meant to learn from.

DesignAI-guided
Partner synthesisMade by partners
Independent labHPLC · Endotoxin
Structured dataEvery result recorded
ModelsIn development
Better designsBack to the start

How it works

Every measurement becomes data.

Design work, synthesis partners and laboratories all produce information: sequences, specifications, chromatograms, endotoxin results. We are building one structured record per batch, so every measurement stays readable and comparable.

Our approach: models that learn from these records and help decide what to design and make next. People make the decisions. The models are meant to make sure nothing gets overlooked.

Peptides and AI

Data first. Then models.

Peptide quality is decided in the laboratory, and the laboratory produces data. We are building tools that read sequence, structure and analytical data together, compare each batch with its history and help choose which variants are worth making. People make the final call.

Our capabilities

Readable results

Chromatograms, mass spectra and endotoxin reports usually arrive in different formats. We are building tools that turn them into structured data, so nothing stays buried in a PDF.

Earlier signals

Our aim: quality and stability questions that become visible in the data before the next batch is made, not after.

Better next designs

We want every measurement to inform the next design, so each round starts better informed than the one before.