Optimization Core
Bayesian and multi-objective engines
- Gaussian process optimization with uncertainty-aware recommendations
- Multi-objective strategy support for competing scientific outcomes
- Constraint-aware search inside real experimental bounds
Features
A scientific optimization platform, not a generic dashboard
AcquiLAB connects analysis, optimization, and AI workflows into one coherent operating surface for research teams.
Scientific Analysis Layer
From raw file to quantitative signal
- Structured ingestion across spectroscopy and analytical workflows
- Automated extraction of objective-relevant metrics
- Standardized output ready for optimization and reporting
AI Workflow Layer
Guided interpretation and iteration planning
- Grounded AI summaries tied to your uploaded experiment context
- Decision support to prioritize next experiments
- Workflow acceleration for repetitive analysis tasks
Scientific workflows
Purpose-built modules for iterative science
Each surface is designed to reduce friction between experiment execution, result interpretation, and next-step planning.
Analyzer Workbench
Unify routine method execution and quality checks across techniques.
Plot Studio
Generate clean, publication-ready scientific figures from run outputs.
Experiment Tracking
Track objective progression and compare candidate trajectories.
Operational Control
Consistent workflow patterns and traceable experiment records.
Screenshots preview
Current product surface placeholders
Replace these blocks with production screenshots during final launch asset pass.
Feature screenshot placeholder: BO workflow
Feature screenshot placeholder: Analysis panel
Feature screenshot placeholder: Plot Studio export
Explore the full platform with your own workflows
Start with free access and scale when your team is ready for deeper AI-assisted throughput.
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