Question: I need a platform that allows me to deploy and run GenAI and Large Language Models securely within my own infrastructure.

If you need a platform to run GenAI and Large Language Models in your own environment, Zerve is a great option. It lets you run GenAI and LLMs in your own architecture, with a self-hosted option on AWS, Azure, or GCP instances. Some of its features include an integrated environment, fine-grained GPU control, and collaboration tools, which can be particularly useful for data science teams.

Another contender is Lamini, an enterprise-focused platform for software teams to create, manage and deploy LLMs on their own data. It can be deployed in different environments, including air-gapped environments, and offers features like memory tuning for high accuracy and high-throughput inference. Lamini also offers a full platform for managing the model lifecycle from comparison to deployment.

For a more secure, enterprise-focused option, ClearGPT is designed to address security, performance and data governance concerns. It prevents data leakage and provides maximum control over corporate IP, making it suitable for internal enterprise use. ClearGPT offers role-based access and data governance, with a human reinforcement feedback loop and continuous fresh data for adaptable AI, for the highest model performance and lowest running costs.

Last, you could look at Dayzero, which promises hyper-personalized applications powered by custom LLMs running securely in your environment. Dayzero offers products like Worx for training and deploying generative AI models, Altimo for intelligent dialogues and content creation, and Blox for automation. It focuses on precision pre-training and custom application development, so AI models are trained for specific domains, and it can integrate with a wide variety of data sources and inference endpoints.