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Also, For what it’s worth, this can be deployed both on-prem and in the cloud. Different teams have different constraints, so we’re trying to stay flexible on t
by pveldandi 10mo ago
Also, For what it’s worth, this can be deployed both on-prem and in the cloud. Different teams have different constraints, so we’re trying to stay flexible on that.
- pveldandi 10mo agoHappy to dig deeper and show how exactly it works under the hood. For context, here’s the main site where the architecture and deployment options are explained: https://inferx.net/ https://inferx.net/
- verdverm 10mo agoI don't personally have this problem. One of my clients does, so my questions are ones I'd expect the CTO to ask you in a sales call. They already have an in-house system and I suspect would not replace it with anything other an open source option or hyperscaler option. Are you going to make this open source? That's the modus operandi around Ai and gaining adoption for those outside Big Ai (where branding is already strong)
- pveldandi 10mo agoIt’s an open-core model. The control plane is already open source and can be deployed fairly easily. We’re not trying to replace in-house systems or hyperscalers. This can run on Kubernetes and integrate into existing infrastructure. The runtime layer is where we’re focusing the differentiation.
- pveldandi 10mo agoIt’s an open-core model. The control plane is already open source and can be deployed fairly easily. We’re not trying to replace in-house systems or hyperscalers. This can run on Kubernetes and integrate into existing infrastructure. The runtime layer is where we’re focusing the differentiation.