Explore Our Custom Machine Learning Models
From stock forecasts to manufacturing optimization, our ML models show what’s possible when data becomes intelligence.
Stock ML
📈 Stock Market Forecasting with Neural Networks
Everyone watches the market. We build neural networks that forecast the next move.
Process ML (PML)
⚡ Plasma Etch Rate Prediction
A deep learning model trained on a physics-inspired surrogate equation representing plasma etching, a core process in semiconductor manufacturing. This demo shows how machine learning can support precise rate prediction and ultimately enable smarter process control on advanced equipment.
🚀 Try the Plasma Etch Prediction Model →
📖 Read the article →
🧪 CSTR Surrogate Model
A neural network model trained on the classic Continuous Stirred Tank Reactor (CSTR) system. This demonstration shows how even a well-understood process can benefit from data-driven simulation and rapid what-if analysis.
Business ML (BML)
💊 Pharma Process Cost Estimation
A Business ML model trained on a synthetic paracetamol production dataset to estimate process costs. This proof-of-concept demonstrates how neural networks can outperform spreadsheets in accuracy, flexibility, and insight.
🚀 Try the Paracetamol Model →
📖 Article under publication review at AIChE
🧮 CMOS Cost Modeling
A Business ML model trained to estimate multi-step cost components in CMOS semiconductor fabrication. This work highlights the potential of neural networks to replace static formulas and improve margin clarity in high-variability operations.
🚀 Model under live deployment migration
📖 Read the Article →
Healthcare ML
🧬 Breast Cancer Diagnostic Model
Explore our proof-of-concept AI/ML model for medical diagnostics — a neural network trained to predict breast cancer outcomes based on key clinical features. This example demonstrates how machine learning can support early detection and assist in clinical decision-making by learning patterns from labeled diagnostic data.
While this model is built on open-source data for demonstration, the same architecture and workflow can be adapted to real-world healthcare scenarios using secure, anonymized patient data.
🚀 Try the Breast Cancer Prediction Model →
📖 Read the Article →