Together AI
Build, deploy, and optimize AI models with ultra-fast, scalable solutions.
About
Together AI is a platform crafted for those aiming to leverage advanced artificial intelligence for practical applications and research. Its focus is on providing powerful infrastructure for developing, deploying, and fine-tuning generative AI models, making complex technology accessible to a broad range of users. The platform features rapid inference speeds, scalable resources, and options to customize models for different objectives, whether for prototyping or production-scale systems.
With a selection of GPU clusters and tools for model training and optimization, Together AI streamlines the traditionally resource-intensive process of working with cutting-edge AI models. Developers can tap into open-source projects for greater transparency and flexibility, benefiting from a supportive community and comprehensive technical resources.
Despite its power, the platform may present a steep learning curve for newcomers unfamiliar with AI workflows. It’s best suited to users who require efficiency and the ability to iterate rapidly, such as businesses scaling up AI-driven offerings or researchers exploring novel machine learning approaches.
Who is Together AI made for?
Together AI is ideally suited for technical leads, software engineers, and data scientists in organizations where custom artificial intelligence solutions are key to product development or operational efficiency. Companies developing AI-powered applications, such as startups experimenting with new generative models or enterprises deploying large-scale machine learning infrastructure, will benefit from the platform's scalability and speed.
Academic research teams tackling cutting-edge AI topics can leverage the platform’s open-source tools and configurable resources to run experiments efficiently. Additionally, independent developers and consultants building bespoke models for clients across industries—from gaming to social impact projects—can utilize Together AI to reduce infrastructure overhead and accelerate iteration cycles.
It is particularly beneficial for organizations already experienced with AI workflows, as it enables rapid deployment and optimization of models, but may be less accessible to absolute beginners due to its advanced feature set.