Platform

PyTorch and TensorFlow

Deep learning frameworks for custom models. We help organisations build, train and deploy custom AI models using PyTorch and TensorFlow for tasks that require bespoke architectures.

Strengths

What makes these frameworks different

PyTorch and TensorFlow provide the foundation for custom deep learning when pre-built models do not meet your requirements.

Custom model development

Build bespoke neural network architectures tailored to your specific data patterns and business requirements.

Production deployment

Proven track record with enterprise deployments. TensorFlow Serving, TorchServe and ONNX for scalable model serving.

Research to production

Active community and extensive documentation. Seamless path from research prototypes to production-grade models.

Applications

Use cases for PyTorch and TensorFlow

Computer vision

Image classification, object detection, segmentation and visual inspection models for manufacturing and retail.

Natural language processing

Custom text classification, entity extraction and language understanding models trained on domain-specific data.

Time series forecasting

Predictive models for demand forecasting, financial modelling and operational planning from historical data.

Anomaly detection

Custom models that identify unusual patterns in manufacturing, financial transactions or system behaviour.

Model fine-tuning

Fine-tune foundation models on proprietary data for domain-specific performance improvements.

Edge deployment

Optimise and deploy models to edge devices using TensorFlow Lite, PyTorch Mobile and ONNX Runtime.

Frequently Asked Questions

Should we use PyTorch or TensorFlow?

PyTorch is preferred for research and rapid prototyping. TensorFlow offers stronger production serving and edge deployment tools. We help you choose based on your specific requirements.

How can The Bot Forge help with implementation?

Our team provides end-to-end support, from model architecture design and training to production deployment and ongoing maintenance.

What are the typical use cases?

These frameworks are commonly used for computer vision, NLP, time series forecasting, anomaly detection and custom model development when pre-built solutions do not fit.

Build Custom AI Models

Ready to build bespoke AI models for your business? We can help you design, train and deploy with PyTorch and TensorFlow.