AI / Machine Learning
PyTorch & AI
PyTorch (alongside Keras where appropriate) is used to train, fine-tune, and deploy custom AI models for computer vision, motion analysis, and prediction tasks, rather than relying solely on third-party APIs for capabilities that need to run on proprietary data.
When it’s the right fit
Custom model training is appropriate when a project needs behavior a general-purpose API cannot provide: a specific data domain, tighter latency or cost control, or a model that needs to run without sending data to a third party. For simpler needs, LFT Industries integrates existing AI/LLM APIs directly instead of training from scratch.
How it fits the rest of the stack
Trained models are typically served through a FastAPI or Laravel inference endpoint, deployed on AWS, and consumed by a React or React Native frontend so the AI output reaches users through a normal product interface.
Evidence
Where this shows up in real work
AI Rehabilitation & Motion Analysis Platform
A web application for rehabilitation-oriented movement analysis, combining motion capture with AI-assisted feedback.
AI-Powered Fitness Coaching Platform
A cross-platform fitness coaching product with mirrored mobile and web experiences and AI-assisted personalization.
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