RoBiome provides a physical AI platform that continuously collects sensor data from biomanufacturing equipment and uses machine‑learning models to automatically adjust process parameters. The system reduces cycle times, material waste, and quality variability for biopharma manufacturers by delivering real‑time control, predictive analytics, and an operator dashboard that integrates with existing hardware.
Funding
Funding not disclosed
Founders
Product
Problem
Biologics manufacturers often face long production cycles, high material waste, and difficulty maintaining consistent product quality due to manual process control and limited real‑time insight.
Solution
RoBiome offers a physical AI platform that continuously ingests sensor data from biomanufacturing equipment and applies machine‑learning models to adjust process parameters on the fly. By automating control loops, the system shortens cycle times, reduces waste, and keeps critical quality attributes within target ranges. The platform integrates with existing hardware, requiring no major equipment overhaul, and provides operators with a dashboard that visualizes key performance metrics and recommended actions. This enables manufacturers to increase overall throughput while preserving product integrity.
Target Audience
Primary customers are biopharmaceutical companies and contract manufacturing organizations that produce therapeutic proteins, antibodies, and other biologics at scale.
Features
- Real‑time data acquisition from temperature, pH, dissolved oxygen, and other process sensors
- AI‑driven control algorithms that automatically optimize feed rates, agitation, and other critical parameters
- Predictive analytics to forecast batch outcomes and flag deviations before they impact quality
- Seamless integration with standard bioprocessing equipment via open APIs
- Operator dashboard with actionable insights and alerts for rapid decision‑making