Carton — Run ML models in any language

Carton is a machine learning runner for executing models across any programming language for developers and engineers

Carton is a machine learning runner that allows developers to execute any ML model from any programming language without managing complex dependencies. This tool is designed for software engineers and data science teams who need to deploy models into production environments where the original training language might not be supported. By providing a unified interface, Carton eliminates the friction typically found when moving research code into a stable application backbone. The platform handles the backend heavy lifting by providing a stable API for multiple languages including C++, Rust, and Python. Business owners will find Carton valuable because it reduces the technical overhead and specialized hiring previously required to bridge the gap between data science and software engineering. It creates a standardized environment where models from frameworks like PyTorch or TensorFlow run consistently regardless of the host application. On surfai.app, we track tools like this that simplify the technical stack for scaling startups. Carton includes features for real-time debugging and visualization, making it easier for teams to verify model performance during the integration phase. It also offers automatic updates to ensure libraries remain current without manual intervention. The infrastructure is built to scale, supporting large datasets and high-traffic applications. This ensures that as a business grows, the ML deployment process remains stable and predictable. Currently, Carton offers a freemium model that allows teams to start implementing models at no initial cost before scaling to enterprise-level requirements in 2026.

• Pricing: freemium

Specifications

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