We have demonstrated that we can solve difficult antibody engineering problems that stall in traditional discovery and optimization because they demand best-in-class complex modalities (e.g., multispecifics) or tough epitopes, and be highly developable. Our automated, AI-driven wet lab runs tight design-build-test cycles that optimize multiple parameters at once, delivering your next high-value development candidate faster, leading to a faster, higher probability path to the patient.

BigHat partners with leading biopharma and frontier AI teams to build fit-for-purpose datasets to rapidly improve today’s leading models and agents. We act as a full service data generation partner with industry-leading cycle times (1-2 weeks), broad offerings across formats and properties, custom data pipelines, and active-learning strategies to maximize value per token at scale. We also develop, train, and customize AI/ML models that predict key antibody properties. Our platform seamlessly turns complex biological assays into reliable, AI-trainable readouts to deliver high-fidelity data at the scale across 20+ assays and every major antibody format.

BigHat has its own pipeline of engineered antibodies aimed at validated, high-value targets. We out-license preclinical and clinical-stage assets to partners equipped to carry them through development to patients.