Use your data to train your models. Your team can use its experimental data to develop and improve internal models.
Optimizer for Biotech
Get your assay working. Keep it working
Choose what to test, design more informative plate-based
experiments, and use each
result to guide the next run.
Spend fewer runs finding the right conditions
Experiment development depends on decisions about variables, ranges, controls, plate layout, and performance targets.
The Optimizer brings those decisions into one workflow, so teams can test conditions systematically, prepare run-ready outputs, and carry what they learn into the next experiment.
From experimental goal to next run
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Define
Bring in the protocol, biological question, performance targets, prior data, and known constraints.
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Design
Choose the parameters, ranges, controls, and conditions worth testing.
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Prepare
Generate condition tables, plate maps, protocols, and automation-ready files.
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Learn
Connect results to the conditions that produced them and decide what to test next.
Generate the data your models need
Historical data is often too limited or poorly matched to the problem a biotech team is trying to model.
The Optimizer helps teams develop reliable, high-throughput assays that generate fit-for-purpose experimental data for training and improving their own models.
Your data does not train ours. Potato does not use your protocols, results, or generated outputs to train or improve its own models.
Built for lean scientific teams
Research leaders
Reduce avoidable optimization cycles and preserve the experimental record as programs, teams, and partners change.
Assay scientists
Test multiple factors efficiently and understand why each condition performed the way it did.
Automation teams
Work from plate maps and execution files designed around instrument constraints.
Built for plate-based workflows
ELISA optimization · Cell-based assay development · Media optimization · Screening
preparation · Assay development · Bench-to-automation transfer
Move the next assay forward
Early access is open to a limited number of biotech teams running plate-based endpoint assays. If your scientists are spending too much time on optimization cycles that could be shorter, or rebuilding experimental context every time a new assay starts, we'd like to show you what a more structured approach looks like in practice.
Request Early Access