The Tough Tech problem we are solving
Biomanufacturing teams are flooded with fragmented, inconsistent data across experiments, instruments, and scales, making it hard for AI to reliably learn from processes and drive better outcomes. As a result, developing and scaling biologics and other bio-based products still relies heavily on trial-and-error experimentation, slow iteration, and underused process knowledge, which delays therapies and keeps costs high. Bioqore is solving the bottleneck of unstructured bioprocess data and inefficient workflows so that AI can become a dependable engine for faster, more scalable biomanufacturing.
About our solution
Bioqore provides an AI-native layer for biomanufacturing that unifies biological and process data, builds purpose-built models, and connects to automation so small teams can operate like world-class process groups. Its proprietary models are trained specifically on bioprocess data and continuously improved with real lab experiments, enabling the platform to predict outcomes, recommend optimal conditions, and support real-time process optimization from lab scale through scale-up.