Assayla.
Simulate it. Then run it.
A digital twin and robotic orchestration layer that converts scientific plans into validated machine steps, tests them virtually, executes them on lab automation, and records every physical action.
The physical experiment is still the slowest break in the AI loop.
Sciento can design a protocol, but a person still has to translate it into instrument-specific steps, catch physical constraints, handle scheduling, and manually return the outcome. That makes execution slow, variable, and difficult to learn from.
Assayla is designed to simulate the workflow before reagents are spent, coordinate compatible automation, stream observations back through Scopea, and preserve the exact sim-to-real record.
A control plane for automated experiments.
Lab digital twin
Model instruments, deck layouts, timing, material movement, and workflow constraints.
Protocol compiler
Translate co-scientist plans into validated, machine-readable execution steps.
Robotic orchestration
Coordinate liquid handlers, plate movers, incubators, readers, and connected systems.
Pre-run optimization
Estimate reagent cost, scheduling conflicts, and likely failure modes before execution.
Closed-loop control
Use Scopea measurements to support mid-run adjustments and next-step decisions.
Physical audit trail
Record commands, device state, sensor output, overrides, and results for GxP evidence.
Close the gap between protocol and physical result.
Make the plan executable
Resolve steps, dependencies, resources, and instrument commands.
Dry-run the workflow
Test timing, motion, collisions, material flow, and cost.
Orchestrate the lab
Execute against connected automation with bounded policies.
Compare sim to real
Return observations and discrepancies to the scientific loop.
Physical AI for a high-value scientific environment.
The physical arm of the Sciento loop.
Connect one automated workflow end to end.
Start with a bounded instrument workflow and build the sim-to-real dataset from day one.