AUXO delivers an autonomous, real‑time bioprocess control platform that combines continuous in‑line biosensing with AI‑driven closed‑loop feed strategies. The stack integrates edge AI inference, hybrid mechanistic‑ML models, and GMP‑ready compliance to optimize glucose, lactate, glutamine, glutamate, and ammonia levels across benchtop to pilot‑scale bioreactors, reducing harvest loss and development time for pharmaceutical manufacturers, CDMOs, industrial fermenters, and research labs.
Funding
Funding not disclosed
Founders
Product
Problem
Biomanufacturing processes rely on intermittent offline assays and manual feed adjustments, leading to delayed detection of deviations, harvest loss of 5‑10%, and long development cycles of 12‑24 months for new strains.
Solution
AUXO delivers an integrated bioprocess control platform that combines continuous in‑line biosensing with AI‑driven closed‑loop control executed on edge hardware located on each bioreactor. Hybrid mechanistic‑ML models learn across batches and generate sub‑second feed‑strategy and set‑point adjustments, while maintaining 21 CFR Part 11 compliance. The platform operates offline and synchronizes model improvements, enabling real‑time monitoring, autonomous decision‑making, and rapid process optimization from bench‑scale to pilot production.
Target Audience
Primary customers are pharmaceutical manufacturers, contract development and manufacturing organizations (CDMOs), industrial fermentation operators, and research institutions seeking real‑time, automated bioprocess control.
Features
- Continuous in‑line biosensors measuring glucose, lactate, glutamine, glutamate, and ammonia via standard instrument ports
- Closed‑loop AI control that autonomously adjusts feed strategies and process setpoints based on hybrid mechanistic‑ML models
- Edge AI processing unit providing sub‑second inference locally per bioreactor, with offline capability and model sync
- Modular bioreactor hardware (AUXO V) available in benchtop (2‑15 L) and pilot (100‑250 L) volumes, manufactured to GMP standards
- GMP‑ready architecture with 21 CFR Part 11 compliance, supporting PAT, IQ‑OQ‑PQ, and validated production workflows
- Fleet‑level learning that aggregates data across multiple reactors to improve yields and reduce downtime