If you're looking for another Zerve alternative, Anyscale is a top option. The platform is geared for building, deploying and scaling AI models, with a promise of top performance and efficiency. It can handle a broad range of AI models, including LLMs, and can run in a variety of cloud environments as well as on-premises. Anyscale has security and governance controls, making it a good option for enterprise customers, and it has native support for popular IDEs and persisted storage.
Another option worth considering is ClearGPT, an enterprise-focused platform for internal use. It's designed to handle security, performance and data governance issues while delivering the best model performance and customization. ClearGPT has no data leakage and supports role-based access and data governance, so it's a good option for companies that want to build AI internally without vendor lock-in.
If you need to fine-tune and serve large language models without breaking the bank, Predibase is a good option. It can fine-tune open-source LLMs and offers a relatively low-cost serving foundation that's SOC-2 compliant. With support for techniques like quantization and low-rank adaptation, Predibase is a good option for a variety of AI tasks, including classification and code generation.
Last, DataRobot AI Platform combines generative and predictive workflows, letting you innovate quickly and tap into a deeper ecosystem. It's a leader in the 2024 Gartner Magic Quadrant for Data Science and Machine Learning Platforms. DataRobot speeds up AI project delivery with its enterprise-grade governance and monitoring. That's a good option for teams that want to improve productivity and control.