Machine Learning Models
Custom models trained on your data. Deployed to your infrastructure.
Generic AI APIs give everyone the same output. We build models trained specifically on your data — so they understand your customers, your products, and your edge cases. From data preprocessing to production deployment, we own the full pipeline.
Who This Is For
You might need this if:
- ✅ You want to predict which customers are likely to churn
- ✅ You need to classify documents, images, or signals automatically
- ✅ You have historical data and want to predict future outcomes
- ✅ You need to detect anomalies or fraud in transactions
What we deliver:
- Trained production model (saved weights + pipeline)
- REST API endpoint for inference
- Accuracy & performance benchmark report
- Jupyter notebook with full training walkthrough
- Deployment guide for your infrastructure
- 30-day post-launch support
Models We've Trained
X-Pathology — Colon Cancer Prediction (97.33% accuracy)
EfficientNetB1 model for 9-class colorectal histopathology classification. Temperature calibration, Grad-CAM++ interpretability, domain-specific CTransPath backbone.
Plant Disease Detector (98.75% accuracy)
CNN model detecting 38 different plant disease types. Trained on 87,000 images with heavy data augmentation and label smoothing.
RNN Forecasting Benchmarks
Comparative evaluation of GRU, Stacked, and Bidirectional RNN architectures for continuous time-series forecasting on real-world sensor data.
Frequently Asked Questions
I don't have a lot of data. Can you still build a model?
It depends on the problem. For many classification tasks, a few hundred to a few thousand labelled samples is enough. We'll audit your data in the discovery call and tell you honestly whether ML is the right approach.
What kinds of problems can machine learning solve?
Predicting customer churn, classifying images or documents, recommending products, detecting anomalies in sensor data, forecasting demand — any problem where you have historical data and want to predict future outcomes.
Do I need to understand ML to work with you?
Not at all. We handle the technical work. You need to understand your business problem and have access to your data. We translate the rest into plain English.
What frameworks do you use?
TensorFlow, PyTorch, Keras, scikit-learn, and XGBoost — depending on the problem. We choose the right tool for each task, not the trendy one.
Ready to Train Your Model?
Send us your data (or describe it), and we'll tell you what accuracy is realistic and what the full build would involve.
Book a Free Strategy Call