Technology
Process Superintelligence
DecaOS turns every experiment and every batch into learning, so designing a process and running a plant finally become one loop.
Explore DecaOSDecaOS
A new model for product development and optimization
Industry is the ultimate data generator. Every batch, every deviation and every lab result creates process knowledge that has never existed before, yet most of it is never used to learn. DecaOS is trained on that knowledge, from the lab bench to the plant floor, and reasons over it the way a process engineer does: from first principles and real evidence.
A self-learning engine grounded in physics and real process data
- 01
Process Models & Tools
Expand what DecaOS can predict and test before anything is built.
- 02
Autonomous Experiments
Self-driving labs and live plant signals provide real-world feedback.
- 03
Continuous Process Optimisation
DecaOS learns your process with every run, and keeps improving it.
Across unit operations
One system for the steps that decide yield, quality, energy use and CO₂.
- Reaction
- Distillation
- Crystallisation
- Drying
- Fermentation
- Filtration
- Heat transfer
- Granulation
- Mixing
- Extraction
Self-driving labs
An extensible network of instruments built for AI-driven process development
Automated reactors, analytics and pilot equipment run the experiments DecaOS designs, around the clock. Every run is measured, checked and fed straight back into the model, and the same loop carries on into the plant once a process scales up.
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The DecaPlants Innovation Engine
Inputs
Process Data
Every hypothesis, experiment, measurement and batch record becomes new training data. Each run adds process knowledge that did not exist before, from the lab bench to the plant floor.
Verifiers
In process engineering the ground truth is physical. Lab analytics, pilot runs and plant KPIs check every prediction and reward what actually works, so the model learns from reality, not guesses.
Process Tools
Hard process problems need the right tools: process simulators, kinetic and thermodynamic models, property data and robotic lab workflows. DecaOS chains them together to design and test each step.
Design Targets
Yield, quality, energy and CO₂ are set as targets from the first run, not checked afterwards. Every learning step moves the process towards one that is cheaper and cleaner to run.
Outputs
Processes Get Smarter
What DecaOS learns on one process carries over to the next: across unit operations, products and sites, not just one line.
Development Gets Faster
Experiments run in parallel and around the clock, cutting the time from a first idea to a validated process that is ready to scale.
Plants Get Cleaner
Plants run closer to their optimum every day, using less energy, emitting less CO₂ and losing fewer batches.
Scaling self-driving labs and self-learning plants
DecaPlants is building an autonomous lab where AI proposes, runs and learns from experiments at ever higher throughput. Each self-driving lab brings the DecaOS reasoning model, process tools, automation and verifiers together in one loop. Every experiment feeds a shared model, and every connected plant adds operating data from the real world. The more the loop runs, the better it designs, scales up and operates processes, for each customer and for industry as a whole.