Question: I'm looking for a way to integrate AI models into my application without managing complex infrastructure, do you know of any solutions?

If you want to use AI models in your app without worrying about the underlying infrastructure, Instill could be a good option. It's a no-code/low-code AI platform that takes care of data, models and pipelines so you can concentrate on iterating AI use cases instead of infrastructure. Instill offers features like speech responses, webpage summarization, visual assistance and object detection, with dynamically generated inference API endpoints for easy deployment. It has Python and TypeScript SDKs and tiered pricing to accommodate different needs.

Another option is the AIML API, which lets you tap into more than 100 AI models through a single API. The platform is designed for high scalability and reliability, with serverless inference and a simple, predictable pricing model based on token usage. It's geared for more sophisticated machine learning projects that need fast, reliable and cost-effective integration with a wide range of AI models.

Keywords AI is a unified DevOps platform for building, deploying and monitoring AI applications based on large language models. It offers a single API endpoint for multiple LLM models, can handle concurrent calls with no latency and can be easily integrated with OpenAI APIs. The platform includes tools for rapid development, performance monitoring and data collection, making it a good fit for AI startups that want to focus on building products rather than infrastructure.

For those who want a low-code option, UBOS lets you build custom Generative AI applications directly in your browser with no setup required. It supports a wide range of AI models, including LLMs like ChatGPT and Llama 2, and offers features like single-click deployment and collaborative workspaces. UBOS is designed for both technical and non-technical users, so it's good for startups and enterprises.