Launching today
Huddle01 Cloud
Deploy your AI Agents in 60 seconds
987 followers
Deploy your AI Agents in 60 seconds
987 followers
Setting up OpenClaw shouldn't take hours. Deploy a fully managed & secure version of Openclaw in 60 seconds! We take care of infrastructure, AI inference & updates so you can focus on building your agents - not keeping them online. Train your agents, not your hosting skills.
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Launch Team / Built With
The Docker Sandbox approach is really smart. Getting VM-level isolation with container speeds is the kind of tradeoff that actually matters when you're running agents that need to hit external APIs and handle real data.
Curious about one thing though, how does cold start look? Like if an agent hasn't run in a while, does it spin up instantly or is there a warmup period? That's usually where managed platforms trip up.
Huddle01 Cloud
@mihir_kanzariya For Openclaw to work we need to keep docker container running, we don't shut them down
Huddle01 Cloud
@mihir_kanzariya Our VMs run on secure & extremely fast hardware level virtualisation which bring the best performance for the underlying Agents running in sandboxes
Also agents are always warm in our case as they are always running
Huddle01 Cloud
Heyloo Product Hunt 👋
I’m Arush, and I lead Cloud Infra here at Huddle01.
Having spent the last six years building and scaling infrastructure, I’ve seen the same story play out over and over: Start on Public Cloud, get traction, scale up, and then hit a wall when you realize your cloud bill has officially eclipsed your payroll. You end up in what r/DevOps calls "hyperscaler jail", locked into proprietory services and predatory vendor mechanisms that make migrating feel impossible.
That’s exactly the predicament we faced when building our global video infrastructure, As we scaled to 250,000+ users on our real-time communication platform, our Cloud bills went through the roof. We weren't just paying for compute; we were paying for insane markups that didn't make sense for a growing company.
So, we decided to build what we actually wanted: the "Dream Cloud Provider."
That's when we discovered the concept of bare metals. Bare metals are real servers you can buy and run your own infrastructure on and realise that the margins these cloud providers are making are insane.
We spent years cracking deals with data centers and negotiating with GPU providers to tie fast, physical infrastructure into a platform that offers the flexibility of the cloud with the transparent billing of on-prem. We battle-tested this internally for two years to power our own RTC services, and today, we’re finally opening it up to the public.
Huddle01 Cloud today delivers the same baremetal performance with the elasticity offered by cloud with SOC 2 Compliance.
For the AI companies building today with "hockey stick" growth, this is a game-changer. You shouldn't have to choose between fast deployment and sustainable margins. We’ve handled the heavy lifting, the physical infra, networking, security & compliance so you can deploy high-performance workloads (like the 1-click OpenClaw agents we're showing off today) in under 60 seconds without touching a terminal.
I’m here to answer any technical questions about our stack, how we’ve optimized for low latency, or how to escape the "cloud tax" while you scale.
Let’s build something that scales on your terms, not the hyperscaler's. 🚀
Impressive speed to deploy — 60-second setup is a strong pitch. Curious though: how does the managed infrastructure handle custom tool integrations or private data sources that agents might need to access? And is there a way to inspect or audit the AI inference logs for debugging? That visibility would be a big deal for production use cases.
Huddle01 Cloud
@lumm Great Questions!!
A title technical but we use something called as Docker Sanboxes which gives openclaw the power of a Virtual Machine and all the security and speeds of a Docker Container, All the Containers have direct access to the internet using Public IPv4 with unlimited egress
So any skill will always have access to the internet and using NVMe drives will have access to local data as well
As for AI Inference logs yes, you can view everything end to end on the dashboard itself
Let me know your feedback when you try out the product
The setup time problem is so real half the people who would actually benefit from open source agent frameworks never get past the infra setup. How does the managed version handle custom model integrations, or is it locked to specific providers?
Huddle01 Cloud
@thyme1 thats the best Part about the setup. When you deploy an agent on Huddle01 Cloud, you get a whole VM with IPv4 attached. You can always SSH to that VM and you can play with any kind of custom model integration, because OpenClaw allows you to do that.
If you don't want to do it, it's one click deploy, choose any of the model providers and it's done for you. So there's never a integration problem and we never force you to use our AI inference. You are free to choose whatever you want to.
Huddle01 Cloud
@thyme1 we provide a framework to get you started very fast on the agent - we use a secure but vanilla version of openclaw , so all openclaw plugins should directly work and have first class support
FuseBase
Interesting wedge - start with the infrastructure pain (which is real and documented) and layer agent deployment on top as the entry point for non-devs. Makes sense as a GTM. What's the target customer right now - individual builders, startups, enterprise?
Huddle01 Cloud
@kate_ramakaieva Huddle01 is targeting the market between hyperscalers and cheap VMs. That's where the sweet spot is.
Huddle01 Cloud
@kate_ramakaieva hii Kate!
we have two main categories we look at
1. hackers & early stage founders : cater to being able to deploy and iterate fastt without worrying about infra
2. mid & large sized companies : who already know their scale & now are looking to switch to a performant but cost effective option
hyperscalers may make sense for startups who are figuring out their scale but is too expensive for companies who already know their scale and now looking to optimise
Hey Ayush! It's really impressive. Is it similar to KimiClaw? What's the main differentiation??
Btw, a quick suggestion build a parallel pricing made for founders, not for devs. I could understand it but I know many founders won't. Hope it's helpful
Huddle01 Cloud
@german_merlo1 hiii german
We specialise in running ai infra at scale , so running agents is a breeze
devs can use their own keys or leverage hudl ai inference to power their agents
kimiclaw is specific to the kimi model - marketing gimmick for kimi tbh
at Huddle01 Cloud you can select any model
Huddle01 Cloud
Hey @german_merlo1
Kimiclaw gives you all that OpenClaw Primitives and its amazing for a certain usecase, we think Openclaw is the new Linux and we want to make it super easy for people to deploy it don't have to think about AI Inference and billing and everything stays in one place
For security we use Docker Sandbox which gives you VMs and all the additional security of docker containers.
We right now have super simple Pricing and just show the bare pricing, but I get the point we can give more details around it
Thanks for commenting and do checkout the product
AutonomyAI
Solid launch, I'm curious how the 60-second OpenClaw deploy works, can't wait to try it! also shared with the team, best of luck!
Huddle01 Cloud
@lev_kerzhner A bit technical we use something called a Docker Sandboxes, which gives you the power of a Virtual Machine with the speed and security of a Docker Container
This is why 60 seconds deployment is possible, but even more than that you get access 200+ models using our AI Inference, so openclaw will have the best model to choose for every query
Huddle01 Cloud
@lev_kerzhner Thanks Lev. Do try and let us know how it goes. Sharing this quick guide we created on the same:
Huddle01 Cloud
@lev_kerzhner thanks a ton lev!
waiting for you and the team to try it out & let us know!