AILaaS is your complete AI lab in the cloud. Instead of building an expensive AI lab on campus, AILaaS gets you instant access to powerful AI tools, the latest GPUs, and everything your students, faculties or researchers need for AI research.

Setting up on-premises AI labs in colleges is prohibitively expensive due to the rapid evolution of GPUs, advancements in AI technology, and specialized infrastructure requirements. Maintaining AI hardware also requires skilled system administrators who are hard to find and retain. 

With AILaaS, you eliminate high capital expenditure, costly infrastructure maintenance, and ongoing staffing challenges. Your lab stays future-proof with the latest GPUs and scales effortlessly to meet growing student and research needs.

AILaaS uses a pay-as-you-go model, so you only pay for what you use. Unlike traditional on-prem AI labs, AILaaS eliminates ongoing maintenance costs and reduces high capital expenditures. Additionally, you avoid the costs of GPU obsolescence and upgrades associated with on-prem labs.

Your students get hands-on experience with the same tools and technologies that companies use today. They get access to advanced GPUs, cutting-edge AI models, integrated vector search technologies, and an industry-grade AI / ML development platform that’s used by 3000+ businesses today.

TIR is a comprehensive AI/ML platform that streamlines AI development. Students and researchers can launch instant environments with PyTorch, NeMo, RAPIDS, and Diffusers, or customize their own. They can also build RAG systems with a private knowledge base. TIR allows anyone to easily deploy models using vLLM, TensorRT, Llama Instruct, TorchServe, and NeMo RAG Service.

TIR provides the tools to learn by doing. Students can test their models in the Inference Playground. They can build smart similarity search systems using vector databases. They can build AI-powered apps in GenAI Studio, and a lot more.

Absolutely! Whether you have 50 students or 200+, we've got you covered. Our packages are flexible, so you can choose what works best for your class size and easily adjust as your needs change.

Your faculty gets dedicated resources for their research when students aren't using the lab. They can work on advanced projects, run complex experiments, and push the boundaries of AI research without worrying about technical limitations.