Substrate Alternatives

If you're looking for a Substrate alternative, Anyscale is a good option. It's a platform for building, deploying and scaling AI apps with the highest performance and efficiency. Anyscale is built on the open-source Ray framework, which supports a broad variety of AI models, and it comes with features like workload scheduling, cloud support, intelligent instance management and GPU and CPU fractioning for better resource usage. It also comes with native support for popular IDEs, persisted storage and Git integration, and flexible pricing including a free tier.

Another option is Parallel AI. This relatively new platform is designed to automate business tasks and increase productivity by giving you access to a range of AI models, including GPT-4. With features like Long-Term Memory, AI Knowledge Base and a Workflow Builder, Parallel AI lets you build sophisticated AI workflows and integrate with tools like Slack and Google Docs. It's got security features like AES-256 encryption and TLS 1.2+ encryption, and it offers flexible pricing options, including a free tier, for individuals and businesses of all sizes.

If you want to specialize in generative AI, LastMile AI is a full-stack developer platform designed to help engineers productionize generative AI apps with confidence. It's got features like Auto-Eval to automatically detect hallucinations, RAG Debugger for better performance, and AIConfig to optimize prompts and model parameters. The platform supports a range of AI models for text, image and audio modalities, and it's got a notebook-inspired environment for prototyping and app development. That makes it easier to deploy production apps.

Last, Keywords AI is a unified DevOps platform designed for building, deploying and monitoring AI apps based on large language models. It's got a single API endpoint for multiple LLM models, can handle hundreds of concurrent calls, and can be easily integrated with OpenAI APIs. The platform also comes with visualization and logging tools, performance monitoring and data collection and fine-tuning for optimizing model performance. Keywords AI is designed to make the AI development process easier, letting developers focus on building products instead of infrastructure.