Hyperferm AI connects with existing bioprocess infrastructure and combines AI, fermentation science and process engineering to turn real-time and historical process data into biological intelligence.
It helps manufacturers understand organism health, batch trajectory and process risk - moving from simply monitoring fermentation to anticipating what happens next.
Capture process and biological signals from existing instrumentation.
Capture process and biological signals from existing instrumentation.
Capture process and biological signals from existing instrumentation.
Capture process and biological signals from existing instrumentation.
Capture process and biological signals from existing instrumentation.
Capture process and biological signals from existing instrumentation.
Fragmented signals become one understanding of the run
Integrated process state.
Organism health.
Forecast to harvest.
Ranked recommendations.
Optimisation over time.
The platform links the physical system inside the fermenter to a governed data and modelling layer, then returns approved decisions to the process.
Deployment can match the plant’s equipment, connectivity, latency, governance and data-residency requirements.
Connect probes through available ports and integrate with current control, historian and laboratory workflows.
Use central model management where appropriate and low-latency local intelligence where operations require it.
Support heterogeneous fermenters, controllers, process equipment and plant software across facilities
Live batch state and early warnings. No change to control.
Recommended set-point and feed moves, approved by the operator.
Validated automated control inside agreed limits, fully audited.
Hyperferm AI turns process intelligence into measurable improvements across production, reliability, scale-up, efficiency and commercial performance.
Improve yield, quality and harvest consistency with greater visibility into batch performance.
Identify deviations earlier, reduce rework risk and make intervention more timely.
Carry process intelligence across scales to accelerate technology transfer and commercial production.
Use energy, water, media, feed and equipment more intelligently throughout the process.
Build more reliable production and stronger unit economics as processes become more predictable and efficient.
Learn from every batch by connecting process data, outcomes and operating decisions.