If you want a platform to run and manage LLM prompts as API endpoints without having to redeploy your whole app, Langtail is a great option. It has a set of tools to deploy prompts as API endpoints, monitor production performance with rich metrics, and run tests to prevent unexpected app behavior. It also has a no-code playground to write and run prompts, so it's good for small businesses and bigger enterprises.
Another good option is LangChain, which covers the full LLM application lifecycle from creation to deployment. It includes tools like LangServe to deploy APIs with parallelization and fallbacks, and LangSmith to monitor application performance. LangChain is a good fit for financial services and FinTech companies that want to optimize operations and offer personalized products.
If you want more control over your infrastructure, Zerve lets you deploy and manage GenAI and LLMs in your own stack. Its integrated environment combines notebook and IDE functionality with fine-grained GPU control, so it's a good fit for data science teams that need flexibility and collaboration tools.
Finally, PROMPTMETHEUS is a full-featured platform for writing, testing, optimizing and deploying prompts for more than 80 LLMs. It's got features like composability, history, cost estimation and data export, so you can easily integrate with third-party services like Notion and Zapier. It's good for individual developers and teams that want to develop and deploy their AI apps efficiently.