LFT Industries

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.

Training and evaluating models on project-specific datasets, including movement and motion data
Computer vision tasks such as pose estimation and visual feature extraction
Packaging trained models behind an inference API that a production application can call

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 SystemsAI / ML

AI Rehabilitation & Motion Analysis Platform

A web application for rehabilitation-oriented movement analysis, combining motion capture with AI-assisted feedback.

LaravelReactPythonPyTorch
Mobile AppsAI / ML

AI-Powered Fitness Coaching Platform

A cross-platform fitness coaching product with mirrored mobile and web experiences and AI-assisted personalization.

React NativeLaravelReactAI Personalization

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