Launched this week
Huddle01 Cloud
Deploy your AI Agents in 60 seconds
1.3K followers
Deploy your AI Agents in 60 seconds
1.3K 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
Trufflow
Part of my issue with cloud cost reports is that it doesn't give me granular enough insight to where my spend went exactly. Is there a way to see which agents are spending what percentage of my total cloud spend?
Huddle01 Cloud
@lienchueh Yeah a lot of people asked for it, we have a dashboard to tell you exactly how much you spent on each model if you use Hudl AI
Big congrats to the @Huddle01 Cloud team on the launch. 🚀
I’ve had the chance to watch @ranjan3118 and the Huddle crew build this from the ground up, and the problem they’re tackling is painfully real. What started as a real-time communications platform quickly ran into the same wall every latency-sensitive product eventually hits: traditional cloud bandwidth costs.
Instead of accepting shrinking margins, they made a bold call — build the infrastructure themselves.
That “fine, we’ll do it ourselves” mindset is exactly how great infra companies are born.
Now they’re stacking developer-first tooling on top of it, including 1-click OpenClaw agent deployment. No terminal. No API keys. Agent running in under a minute.
If you're building anything compute-heavy or latency-sensitive — especially out of India — this is definitely worth experimenting with.
Huddle01 Cloud
Thanks for the kind words @sicksickle
60-second deploys for AI agents is a compelling pitch curious how you handle the secrets injection side at deploy time. Are agent environments fully isolated per customer, or is there a shared execution layer? That boundary tends to matter a lot once enterprise teams start asking about it.
Huddle01 Cloud
@avinash_matrixgard Yep you got it correct. Every agent has its own VM so everything inside that VM, all the environment variables and everything, is basically baked into the machine itself so it cannot be exposed obviously.
The way that it goes is very standard. All the environment variables are stored on our services, all encrypted obviously. When the agent deploys it goes and fetches those encrypted files by us from our services and then also queries for a key to decrypt them. Both of them come in and that is where the VM basically decrypts all the envs inside its execution there so it's never exposed. That's pretty standard, how most clouds do it, like Vercel, Env, or any other cloud. We also do the same.
Every VM has its own embedded space. It has its own private IP. It has its own public IP. It had its own DHCP client and its own KVM layer so it's isolated environments and kind of iterating a classic cloud architecture. We are SO2 Type 2 compliant so a lot of these things are pretty solid for us.
Interesting that each agent runs in its own isolated Docker sandbox. Makes sense for security, but curious what happens when you need agents to actually talk to each other? Like if I deploy a research agent and a coding agent and want them to coordinate on the same task — is there any built-in way for them to discover and communicate, or would I need to wire that up myself through external APIs?
Huddle01 Cloud
@alan_silverstreams Customer, when you make an account with us, we give you a private IP or a private network and all the agents deployed by you remain on that particular private network. Obviously you can use the private IPs or even the public IPs to talk to one another; it's not a big issue for us. It's pretty standard and we will recommend that you use the private IPs because that way you can use a 25 Gbps private link. It's pretty fast.
Kaily
congrats folks! i'm a non-technical person, and i dont pretend to understand half the terms mentioned in the description. but, i have tried using openclaw by hosting it on a VPS using hostinger. how would this be different/better? i'd love to understand this better if someone can remove all jargon for me.
Huddle01 Cloud
@kritikasinghania There is something called dedicated vCPUs and shared vCPUs so think of it like your laptop. it has eight cores; it can be like 20 people are using those eight cores or it can be two people are using one core, right? If 20 people are using the same core then obviously it would be slow Because now people will also be using your RAM; they will also use your storage; they will also be using your internet. If fewer people use your laptop then it's more for everyone and that is the issue of a noisy neighbor.
When you are hosting it on cheap VMs they are cheap because those clouds are providing you or providing tons of users on the same machine. It's not necessarily a bad thing but they tend to overuse it and overdo it. When you come on Huddle, its dedicated vCPU costs about the same, but you get much better quality, much better services. Now your OpenClaw can run many more Skills; it can do a lot of tasks. That's one thing.
Next is obviously on other platforms they try to force you to use their AI providers. Here you don't need to; you can use any of the API keys from the Claude to OpenAI. You can choose any of your models and you can directly use it. If you want to use us even use that, that's one bigger advantage of them over us, because we are a cloud so we already have access to huge amounts of bandwidth so we give you 3 Gbps unlimited internet.
Callio
Love seeing new cloud infrastructure being built. How are you achieving the cost reduction vs traditional providers, is it mainly hardware efficiency, edge distribution, or a different pricing model?
Huddle01 Cloud
@hmadhsan That's a very good question actually and what I have seen is that, to be honest, cost was never the issue. The issue was that the cloud market is designed in such a way that it feels cheap to you because you are on credits but it doesn't feel cheap to you when you have usage. You have models where these cloud companies charge you markups upwards of 8,000%. All in the promise of high availability and pretty fast responses, like milliseconds, which makes sense for the top 500 companies in the world.
That's one part and the second part is focus. These companies have 200+ services. AWS S3, by far, is the most efficient storage; no one can beat S3 of course but S3 is their gold here. You go to AWS thinking of S3 but then you end up buying Kafka. You end up buying SQS and you end up buying so many other services, which ties you to AWS and now this is where they make the money.
What we have seen is most companies don't need it and they don't even use it. I've seen people running on EC2s using Kafka for their scale, which doesn't make sense. So what we are seeing now are the forms of Neo Clouds, like Vercel, specifically built for deployment of next.js, like Railway, or like Modal, like Daytona, specifically for sandboxes.
That is how we are approaching it: we want to focus on five services which 90% of the companies use and how I can push them to the limit, use damn good hardware, and provide value. First the markups are too high; I can always provide them at a better cost and also keep the cost in such a way that it makes sense to the user and to us as well.
Callio
@itsomg thats really cool, thank you for the clarification! Good luck guys
Congrats for the launch, Does the 60‑second deployment include multi‑region availability, or is that an add‑on?
Huddle01 Cloud
@vedantuttam You can deploy OpenClaw in multiple regions in Europe, in US, even in India.
Huddle01 Cloud
@vedantuttam great question vedant!!
currently agents are local to the region they are deployed in - mostly cause all devs want the lowest latency so choosing a region which is closest to you is something we want to allow users to choose!