Question: I'm looking for a unified computation platform that can handle complex algorithms and data analysis across multiple environments.

If you're looking for a single platform for computation that spans multiple environments and can accommodate complex algorithms and data analysis, Wolfram is a good choice. Wolfram is an integrated platform of algorithms, data, notebooks, linguistics and deployment tools designed to support advanced workflows in R&D, education, data science and enterprise. It offers a range of tools like the Wolfram Language, Mathematica and Wolfram|Alpha Notebook Edition, and offers a free trial along with a wealth of documentation.

Another good option is MLflow, an open-source MLOps platform that simplifies the development and deployment of machine learning and generative AI models. It tracks experiments, logs data and manages models across environments. MLflow supports popular deep learning frameworks like PyTorch and TensorFlow, and you can use it for free, so it's a good option for data scientists and teams that want to improve ML workflow collaboration and productivity.

Anyscale is also a good option for developing, deploying and scaling AI workloads. It features workload scheduling, smart instance management and heterogeneous node control for high performance and efficiency. Based on the open-source Ray framework, Anyscale supports a broad range of AI models, and it's free to use, with pricing that scales flexibly, so it's a good option for a variety of enterprise use cases.

If you're more focused on building AI directly into business applications, Dataiku offers a platform that formalizes data use for superior business outcomes. It offers tools for data preparation, machine learning, MLOps, collaboration and governance, and is designed to support a range of teams and industries. Dataiku is a Leader in the Gartner Magic Quadrant for Data Science & ML Platforms, and offers a free edition and a 14-day trial.