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AcquiLAB
AI platform that analyzes instrument data and recommends the next experiment
- Type
- Product
- Domain
- AI & Automation
- Subdomain
- AI Agents
- Product type
- SaaS
- Stage
- Beta
Availability
Not specified
Pricing approach
freemium
Free tier available; Plus, Pro and Team plans coming soon
Location
Seoul, South Korea
Supporting details
Beta
About
AcquiLAB is an AI platform for experimental R&D that analyzes raw instrument data from spectroscopy, electrochemistry, materials analysis and chromatography using validated scientific code, runs physics and chemistry simulations, and uses Bayesian optimization to recommend the next experiment. Scientists upload instrument files, AcquiLAB processes and visualizes results with method metadata, and suggests optimized experimental designs based on all prior results.
Who it is for
Research scientists and laboratory teams running experimental R&D in chemistry, physics and materials science
Integrations and product details
Supports instrument file uploads from JASCO and similar equipment. Analysis includes spectroscopy (UV-Vis, fluorescence, FTIR, Raman, NMR), electrochemistry, materials (XRD, BET), imaging, and separation & mass spectrometry.
Platforms
Web
Process
How it works
- 01Upload raw instrument files directly as exported from lab equipment
- 02AcquiLAB analyzes data using validated scientific code with units and uncertainties recorded
- 03Platform runs simulations to test experimental ideas before using samples
- 04Bayesian optimization engine recommends the next experiment based on all prior results
- 05Export publication-ready figures with full methodology and citations
Distinctive value
What makes it different
Combines analysis, simulation and optimization in one workspace rather than requiring separate tools
Bayesian optimization runs with simulation in the loop to suggest experiments informed by both measured and modeled data
Validates scientific methodology at each step and explains why analyses fail with specific remediation guidance
Supports 33 analysis methods across six scientific disciplines with recorded method versioning
What it helps you do
Analyze instrument data from 33 methods across six technique families
Export results with citations to Word or LaTeX
Generate optimized experiment recommendations using Bayesian optimization
Record and audit every analysis step with method versioning
Run physics and chemistry simulations from reactors to quantum chemistry
Visualize and edit analysis results with recorded methodology
Useful for
Analyze instrument data from 33 methods across six technique families
Run physics and chemistry simulations from reactors to quantum chemistry
Generate optimized experiment recommendations using Bayesian optimization
Visualize and edit analysis results with recorded methodology
Export results with citations to Word or LaTeX
Record and audit every analysis step with method versioning
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