Applications
One autonomous research system across biological domains.
BioSphereer begins with the desired outcome, then adapts evidence, strategy, experimental design, execution, and optimization to the biological context.
Yeast research
Closed-loop research for yeast-based biological production. Manage targets, host comparisons, process conditions, quality measurements, and iterative optimization.
Protein production
From target protein to optimized research campaign. Define the target, compare strategies, plan experiments, analyze results, and determine the next iteration.
Enzyme research
Explore function, structure, and production together by connecting enzyme targets, structural evidence, outcomes, and iterative optimization.
Synthetic biology
Unify biological objectives, design candidates, laboratory workflows, measurements, and research memory in one environment.
Automated biofoundries
Add a common intelligence, orchestration, data, governance, and optimization layer across laboratory equipment and software.
Yeast-based insulin
See the complete campaign move from objective to the next experiment.
BioSphereer coordinates scientific reasoning, approval, device compilation, machinery scheduling, live monitoring, result analysis, and iteration as one traceable workflow.

Define the biological objective
ORIGIN · ATLAS · HELIXStructure human insulin as the target, constrain the yeast host, connect approved evidence, and compare candidate strategies.

Design parallel experiments
MATRIX · AURACreate a controlled portfolio of expression conditions with controls, replicates, measurements, and explicit information-gain goals.

Authorize and compile
SENTINEL · FORGEApply policy and scientist approval, then compile every operation against the laboratory’s versioned device-capability registry.

Build, schedule, and execute
FORGE · ORBIT · PULSE · TRACERun the approved plasmid build, route barcoded samples between instruments, and coordinate robotic probe handling across yeast cultivation while monitoring telemetry, drift, deviations, and lineage.

Measure, learn, and iterate
PRISM · NOVA · TRACEAnalyze measured quality and expression results, preserve full provenance, and rank the next experimental portfolio for review.
Common operating model
Different biology. One continuous research loop.
Goal → evidence → strategy → experiment → execution → analysis → learning → next experiment.