AI-driven experimental control with CloudLab integration
Axiomatic Measurement combines AI with experimental hardware control to automate the design, execution, and analysis of physical experiments. Through integration with CloudLab and the AX platform, we enable reproducible, optimized experimental workflows.
This approach accelerates research by intelligently exploring parameter spaces, identifying optimal measurement configurations, and ensuring experimental reproducibility.
Leverage Adaptive Experimentation (AX) for intelligent parameter optimization. AX uses Bayesian optimization to efficiently explore experimental spaces and find optimal configurations.
AI suggests optimal experimental designs based on scientific objectives, available resources, and prior knowledge. Generate measurement sequences that maximize information gain.
Direct integration with experimental hardware through CloudLab infrastructure. Control instruments, execute measurements, and collect data automatically.
Full tracking of experimental conditions, instrument settings, and environmental parameters. Every measurement is logged with complete provenance for reproducibility.
Optimize measurement sequences for optical, electrical, and mechanical property measurements
Automated testing and characterization of photonic, electronic, and MEMS devices
Find optimal fabrication parameters through intelligent experimental design
Automated measurement and analysis for manufacturing quality assurance
Bayesian optimization for adaptive experimentation
Remote hardware access and orchestration
Instrument control and data acquisition