Cerebrium

@ihuzaifashoukat, thanks for your comment. A few things about Cerebrium help us stand out from competitors: - Our cold starts are consistently low: We have an average cold start of between 2-5 seconds (Excluding your model loading time). We've invested heavily in this area specifically for our real-time use cases (Like voice). What's great is we've abstracted all of this orchestration complexity. Customers who've ditched their old serverless providers rave about our cold start times. More than that, we even help you optimise your models for better cold start performance. - Iterate quickly in the cloud: We've also made it a point to differentiate in this area. Engineering teams without thier own compute want to iterate quickly. Current solutions offer subsequent build-times of tens of minutes. Because of our intelligent distributed caching mechanisms, we've seen subsequent rebuilds and deployments to live in under 9 seconds. - We've kept it simple: We are unopinionated about implementation, so you don't require special syntax, no decorators, no digging through our documentation for specific implementation details. Python code you can run can deploy on our platform (The only configuration required is through a simple to use toml file along with your python code) - We've got great customer service (Ask our customers): Every single person on our team is dedicated to the success of our customers. We want your models performance to be snappy, your costs to be low and are personally invested in getting you to launch on our platform. Jump on a call with us to see for yourself. - We have a large range of compute options: Each customer's needs, use-cases and workloads are unique, we offer over 12 options at competitive prices and we add new ones shortly after their launch. The above sounds great in theory. I encourage you to give the platform at try or join our communities to see for yourself :)

@navid_aghasadeghi appreciate the support! Been great to support you and the team!

Thanks @brendan_provision 🙏🏼

@vr000m appreciate the suport Varun! Really enjoyed working with you and the team on various applications pushing the boundaries of realtime AI!

Thanks @tamir_shklaz! We appreciate your support!

@rajneesh_soni Thanks for the support!

@aditya_lahiri appreciate the support!