TensorFlow
Google's open-source framework for building and deploying machine learning models at scale.
Discuss your projectTensorFlow gives us a production-grade path from model training to deployment, including mobile and edge deployment via TensorFlow Lite — useful when a client needs on-device inference rather than a server round-trip.
We use it for custom ML models where an off-the-shelf LLM API isn't the right fit — classification, recommendation, and computer vision models trained on a client's own data.
How we use TensorFlow
Custom ML models
Classification, recommendation, or forecasting models trained on a client's proprietary data.
On-device inference
TensorFlow Lite models that run directly on mobile devices without a network round-trip.
Computer vision
Image classification and object detection features built into mobile or web products.
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