Integrate with the most versatile general programming language with amplpy.
Leverage AMPL MP solver interfaces with automatic reformulations.
Bring your data from anywhere - get ready to optimize its potential.
Deploy into your larger systems with multiple options.
Empowering Data Scienctists with AMPL: Optimize, Analyze, and Scale
AMPL provides a robust optimization platform that integrates seamlessly with data science workflows, enabling fast model development, optimization, and deployment in production environments. Whether you’re optimizing large datasets, solving real-world constraints, or fine-tuning models for scale, AMPL empowers data scientists to do more with less effort.
AMPL provides full API support for Python, allowing data scientists to incorporate advanced optimization models directly into their Python workflows. Whether you are building data pipelines, processing large datasets, or experimenting with machine learning models, AMPL’s integration with popular libraries like pandas and NumPy ensures a smooth connection between data science and optimization.
AMPL is designed to integrate effortlessly with your existing infrastructure, ensuring smooth, reliable deployment in production environments. Whether you’re using cloud-based services, on-premise servers, or hybrid models, AMPL fits into your technology stack without disruption.
AMPL’s commitment to long-term stability, security, and support gives businesses the confidence to deploy mission-critical applications without worry. Our comprehensive support ensures that your deployment remains optimized and fully functional at all times.
AMPL’s commitment to long-term stability, security, and support gives businesses the confidence to deploy mission-critical applications without worry. Our comprehensive support ensures that your deployment remains optimized and fully functional at all times.
AMPL & Data Science Tools
AMPL is tightly integrated with some of the world’s most powerful optimization solvers, including Gurobi, CPLEX, and CBC. These partnerships allow data scientists to leverage cutting-edge optimization algorithms that can handle a wide variety of model types, including linear, mixed-integer, and non-linear programming.
This versatility empowers data scientists to choose the best solver for their specific use case, ensuring both flexibility and performance.
Data scientists often rely on interactive environments like Google Colab and Jupyter Notebooks for rapid prototyping and collaborative development. AMPL fully supports these platforms, making it easier for data scientists to incorporate optimization directly into their data analysis workflows.
By embedding AMPL in these familiar tools, data scientists can optimize their workflows without stepping outside their preferred coding environments.
AMPL is designed to work wherever your data and models need to be—whether that's in the cloud, on-premise, or across hybrid infrastructures. This flexibility allows data scientists to deploy optimization models at scale, choosing the best environment for their organization’s needs.
This deployment versatility ensures that AMPL can adapt to any organizational infrastructure, making it a trusted tool for data scientists across industries.
Driving Agility and Innovation
AMPL empowers you to not only solve complex optimization challenges but also accelerate innovation, streamline operations, and unlock new business opportunities. Upgrade your existing decision-making processes, expand into new markets with confidence, and optimize every facet of your operations. Our team of optimization experts and certified partners are ready to guide you through seamless integration and ensure you achieve rapid value with AMPL.