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- hello@quml.ai
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AI & Machine Learning Development

You have data. Lots of it. But right now it's sitting in databases, generating reports no one reads, while your team makes decisions based on gut instinct and outdated spreadsheets.
We build machine learning systems that change that. A retailer we worked with used to overstock by 30%—our demand forecasting model cut that to 8%. A fintech company caught 40% more fraud without increasing false positives. A healthcare provider predicted patient readmissions 6 months before they happened.
The technology matters—PyTorch, JAX, MLX for Apple Silicon—but what really matters is whether the model works with your messy, real-world data and integrates with how your team actually makes decisions. That's where we focus.
- Predictive models that forecast demand, churn, and risk
- Deep learning with PyTorch, JAX, and MLX
- NLP and LLM fine-tuning for your domain
- Recommendation systems that boost engagement
- MLOps pipelines with MLflow, Weights & Biases, and Kubeflow

AI & Machine Learning Development - FAQs
Prediction models (demand forecasting, churn, pricing), classification systems (fraud detection, risk scoring), recommendation engines, NLP and LLM fine-tuning for your specific domain, computer vision for inspection and recognition. If you have data and a decision you need to make, we can probably help.
We test obsessively—cross-validation, holdout sets, A/B testing in production. We use Weights & Biases for experiment tracking and LangSmith for LLM observability. But accuracy isn't enough. We focus on whether the model actually helps your team make better decisions. Sometimes 85% accuracy with explainable results beats 95% accuracy from a black box.
Healthcare, fintech, retail, manufacturing, logistics, hospitality. We've built fraud detection, demand forecasting, quality inspection, patient risk scoring, recommendation systems, churn prediction. Different industries, similar patterns. We bring that cross-industry experience to every project.


