Where machine learning meets the lab
We work with manufacturers, formulators, and quality teams to extract actionable insight from existing data — and translate it into measurable process improvement.
The right workflow for your data
Most process improvement programmes fail not because the data is missing, but because the analytical workflow is wrong. Rigid interfaces, generic tools, and reports written by AI without expert review produce noise, not signal. We build stable, repeatable workflows grounded in well-defined operations — and every output is evaluated by a PhD specialist before it reaches you.
Formulation improvement
Find the ingredient interactions your current analysis is missing
Machine learning can capture non-linear relationships between ingredients and output properties that conventional statistical methods overlook. We analyse your existing formulation data to identify which variables drive performance — and model the fastest route to improvement.
Discuss this serviceWhat you get
- Identify which ingredients and concentrations drive target properties
- Reduce the number of experimental runs needed to reach specification
- Improve batch-to-batch consistency by understanding root causes of variation
- Support reformulation for cost reduction, sustainability, or regulatory compliance
Coatings, adhesives, personal care, pharmaceuticals, food and beverage
Process optimisation
Reduce energy, waste, and variation without new capital investment
Process parameters — temperature, pressure, mixing time, feed rate — interact in ways that are difficult to model manually. We use machine learning to map those interactions from your existing process data, identify the parameter settings that minimise waste and energy use, and detect drift before it becomes a quality event.
Discuss this serviceWhat you get
- Identify process parameter combinations that reduce energy consumption
- Detect process drift early using statistical process control principles
- Reduce solvent and raw material waste through tighter process windows
- Build control charts grounded in your actual process capability
Chemical manufacturing, plastics, coatings, adhesives, industrial processes
Batch and quality data analysis
Turn your quality records into a source of competitive advantage
Batch records, QC results, and process logs contain patterns that are invisible to manual review. We analyse your historical data to identify sources of variation, out-of-specification trends, and the process conditions that correlate with your best and worst batches.
Discuss this serviceWhat you get
- Batch-to-batch variation analysis with root cause identification
- Control chart construction and interpretation for manufacturing QC
- Out-of-specification investigation support with data-driven evidence
- Laboratory QC trend analysis including instrument drift detection
Manufacturing QC, analytical laboratories, soil and water testing, industrial QC
AI-assisted report writing with human review
Reports that are scientifically meaningful — not just plausible
AI can draft reports faster than any human team. But without expert review, it produces text that sounds authoritative and contains errors. Every report we produce is written with AI assistance and reviewed by a PhD specialist for scientific accuracy, correct interpretation, and meaningful conclusions.
Discuss this serviceWhat you get
- Cosmetic safety reports reviewed for regulatory compliance
- Process improvement reports grounded in your actual data
- AI-generated analysis checked for scientific accuracy before delivery
- Clear, actionable recommendations — not generic observations
Cosmetics, personal care, regulated manufacturing, chemical industry
How we work
Start with your data
We begin with what you already have. In most cases, the information needed to improve your process exists in your batch records, QC logs, and experimental data. No new sensors or data collection programmes required.
Find the right workflow
We identify the analytical approach that fits your data structure, your process, and your improvement goal — then build a workflow that is stable, repeatable, and grounded in well-defined operations.
Analyse and model
Machine learning identifies patterns, correlations, and potential changes to ingredients and process parameters. We refine the analysis iteratively until the signal is clear and the recommendations are actionable.
Human evaluation
Every output is reviewed by a PhD specialist for scientific accuracy and meaning. You receive conclusions that are defensible, not just data-derived — and reports you can act on with confidence.
Start with your data
Tell us about your process and your improvement goal. We will identify where machine learning can have the most impact.