HVV AI Nanobody Discovery generates diverse nanobody candidates, applies consistent quality control, and delivers ranked outputs and summaries designed for real selection decisions and wet-lab handoff.
The platform is built around decision clarity. Every run produces a consistent summary, a ranked panel, and export-ready files that teams can immediately review and act on.
Stable totals and summaries that stay consistent during review.
Ranking designed to shorten iteration cycles.
Outputs organized for downstream evaluation and collaboration.
The platform combines sequence generation with structure-aware evaluation to support clearer down-select decisions. Rather than optimizing for raw volume, the workflow emphasizes consistency, ranking stability, and interpretability.
Diverse nanobody candidates are generated from target inputs and campaign settings.
Structural and scoring signals are used to organize candidates for review.
Outputs are ranked and summarized to support selection, not just exploration.
This section can later be paired with a simple 3-step diagram or screenshot without changing the copy.
Final candidates selected after QC and scoring.
FASTA and metadata ready for export.
Key parameters and totals captured for reproducibility.
Sample output available on request.
Tell us what you are working on and your timeline. Early access is limited.
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