Question: Can you recommend a solution that allows me to focus on AI innovation while handling the underlying infrastructure for me?

If you need a service that lets you focus on AI innovation while the underlying infrastructure is taken care of, SciPhi is a good choice. SciPhi is an information retrieval system that abstracts away the complexity of building, deploying and scaling Retrieval-Augmented Generation (RAG) systems. It offers flexible document ingestion, powerful document management and dynamic scaling so you can focus on AI customization. With features like HyDE and RAG-Fusion, and the ability to deploy on-prem or cloud infrastructure using Docker, SciPhi is open-source and well-documented, making it a great choice for developers.

Another powerful platform is Abacus.AI, which lets developers create and run applied AI agents and systems at scale. It can handle generative AI and neural network methods to create LLM apps, AI agents and predictive systems. Abacus.AI has features like ChatLLM, AI Agents and tools for forecasting, anomaly detection, and more. It's designed to make AI more easily embeddable into applications, with a focus on high availability, governance and compliance, so it can be used in a variety of business settings.

If you need a secure and customizable AI platform, check out ClearGPT. This enterprise-grade platform is designed to address security, performance and data governance concerns when using generative AI and LLMs. ClearGPT offers role-based access, data governance and continuous fresh data updates, giving you the most control and corporate IP protection. It's designed for internal enterprise use, automating productivity and enhancing products with AI.

Last, Zerve offers a platform that lets you deploy and manage GenAI and LLMs in your own architecture for better control and faster deployment. It marries open models with serverless GPUs and your own data, offering a unified environment with notebook and IDE functionality. With features like fine-grained GPU control, language interoperability and compute optimization, Zerve is designed to help data science teams balance collaboration and stability, with the option to self-host on AWS, Azure or GCP.