Making GenAI
accessible for everyone
We provide the framework for enterprises to easily build and train
high-performing customized GenAI models and serve them at low cost.
We provide the framework for enterprises to easily build and train
high-performing customized GenAI models and serve them at low cost.
Solution
Solution
Lite LLMOps
Lite LLMOps
Lite LLMOps is a solution that automates and optimizes the entire process of selecting, training, evaluating, and deploying language models for enterprise clients. It offers several tailored solutions for different customer needs at various stages of the LLMOps cycle: the Model Builder solution for customers needing automatic model development, the Model Compressor, Model Accelerator, and Query Router solutions for those looking to reduce serving costs, and the Model Evolver solution for clients aiming to maintain stable performance
Lite LLMOps is a solution that automates and optimizes the entire process of selecting, training, evaluating, and deploying language models for enterprise clients. It offers several tailored solutions for different customer needs at various stages of the LLMOps cycle: the Model Builder solution for customers needing automatic model development, the Model Compressor, Model Accelerator, and Query Router solutions for those looking to reduce serving costs, and the Model Evolver solution for clients aiming to maintain stable performance
Solution 2
Solution 2
Lite Space
Lite Space
Lite Space is a research-friendly, on-premise, and cloud-based AI research and development platform designed to help AI researchers utilize limited GPUs more efficiently and effectively. It provides features necessary for AI research, including team-based GPU quota scheduling, team-based job scheduling, usage reports, and Research Mentoring Agents, thus enhancing research productivity and maximizing GPU usage.
Lite Space is a research-friendly, on-premise, and cloud-based AI research and development platform designed to help AI researchers utilize limited GPUs more efficiently and effectively. It provides features necessary for AI research, including team-based GPU quota scheduling, team-based job scheduling, usage reports, and Research Mentoring Agents, thus enhancing research productivity and maximizing GPU usage.
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200 Rivserside Blvd #18G, New York, USA 🇺🇸
© DeepAuto.ai All rights reserved. Privacy Policy.
Naver D2 Startup Campus, Seoul, South Korea 🇰🇷
200 Rivserside Blvd #18G, New York, USA 🇺🇸
© DeepAuto.ai All rights reserved. Privacy Policy.