Clair is a pre-launch concept and prototype exploring scientist-led laboratory intelligence for connected, traceable omics workflows.
A clean read on the biology you're changing.
Clair is an independent concept and prototype exploring how experimental design, lab workflows, analysis, and interpretation could share one traceable, scientist-led operating layer.
The judgment that makes an assay work rarely reaches the protocol.
That judgment is tacit, while execution and analysis are split across teams—losing signal at every seam.
One experimental thread, from question to interpretation.
Clair is exploring infrastructure that could connect experimental design, lab workflows, analysis, and interpretation while keeping scientific judgment and provenance explicit.
Representative research contexts informing the concept include:
A model for a connected workflow—not a current sample-processing service.
Reduce handoffs without removing scientific judgment.
The prototype explores whether a shared operating layer can make omics workflows easier to coordinate, inspect, and learn from. Cost, speed, and quality targets remain to be tested.
Well-documented experiments should make the system easier to inspect and improve.
The concept treats methods, QC decisions, and provenance as reusable structured evidence. How well that compounds is still under evaluation.
Automate the repetition. Keep scientists responsible for the science.
The goal is bounded, inspectable support for expert work—not the removal of scientific judgment.
Clair asks whether shared experimental context can help scientists coordinate more of a workflow without obscuring judgment, uncertainty, or provenance.
Follow Clair as it develops.
Clair is pre-launch. Get in touch for general conversation about the concept or its research direction.
Prefer email? Write to di.autonomouslab@gmail.com.