Launching today
Huddle01 Cloud
Deploy your AI Agents in 60 seconds
416 followers
Deploy your AI Agents in 60 seconds
416 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
Hey Product Hunt 👋
I'm Ayush, co-founder of Huddle01.
Five years ago, my co-founder and I were building a real-time communications platform. As we scaled, we bled our organisation's runway, not to product, not to people, but to cloud bills. We weren't using 200 services they provided with hidden costs; we needed maybe five. But the markups were brutal - 8000% over actual costs for services like bandwidth. We were paying insane markups to hyperscalers for mid-tier performance.
We looked everywhere for an alternative, something with the raw performance of on-prem, the flexibility of the cloud, and pricing that didn't punish you for growing. It didn't exist. So we built it. Huddle01 Cloud delivers bare-metal performance with the flexibility of the cloud and is SOC 2 compliant.
While we were building for teams that needed high-end infra, AI Agents became real workloads. They are compute-heavy, latency-sensitive, and they need to be always active. Moreover, for non-developers and beginners, terminals and CLIs aren’t the most user-friendly option.
With Openclaw launching, many non-devs couldn’t ride the wave due to the complexity of the setup. We realised our infrastructure was exactly what they needed and thus built a 1-click agent deploy on top of it.
Your agent gets running in less than 60 seconds. Just click on deploy, think of a name for your bot and the skills you want to teach it - without the hassle of managing api keys or Mac minis!
Launch week offer: Upto 64% off with Free AI credits.
We would love to get your feedback and suggestions. Help us build Huddle01 Cloud.
Join our Slack: https://huddle01.com/community
We're here all day. Ask us anything.
@ranjan3118 Love the honesty here!
Cloud bills really do feel like ordering a simple coffee and getting charged for the whole coffee machine.
Glad someone finally said “enough” and built an alternative. Excited to see where Huddle01 Cloud goes 🚀
@ranjan3118 Exactly the markups on Hyperscalers are insane and on bandwidth they charge 8000% markups in some region, and they stack fast in todays Video driven world
I remember Cloudflare did an amazing blog on this https://blog.cloudflare.com/aws-egregious-egress/
Huddle01 Cloud
@ranjan3118 Had so much fun working with the team on this! Excited for people to checkout and give their feedback!
Timelaps
Sounds great! Was wondering the 70-80% cost savings compared to the 'Big Three' (AWS/GCP/Azure). Is this primarily due to the decentralized node structure, and what kind of trade-offs (if any) should developers expect regarding uptime or redundancy when moving from a centralized giant to Huddle01?
@henk_pretorius1 Great Question!!!
The answer is very complex but we can simply it like this, Hyperscalers ( AWS, GCP ) have just huge costs to operate they are earning major money from the Top 500 companies that do need there scale but almost 90% companies don't need 200+ service these guys have and still pay for them
Huddle01 is in the intersection of Hyperscalers and Cheap VMs, we focus on robust servers, use our colocation and years of experience to push the main services like VMs, K8s, GPUs to there limit
And Hyperscalers have insane margins 8000% for some services, all because a promise of reliability which should be by default in todays world with Data Center popping everywhere
So in-short
1. Huddle01 Focuses of Core services optimises to there max
2. We pass on the benefits which we get like unlimited egress to customers
3. We give you servers with specs like AMD EPYC, DDR4 ECC RAM, NVMe Storage which allows you to run 4x the capacity of services that you would on any other service
You can read more here on how a Drone Company uses our NVMe storage for Analytics https://huddle01.com/blog/how-marut-drones-processes-spatial-data-3x-faster-with-huddle-cloud
And also our benchmark against notable hyperscaler
https://huddle01.com/blog/aws-is-charging-you-3x-more-for-slower-compute
Timelaps
@itsomg thanks for the detailed reply. Very useful. Good luck with the launch!
@henk_pretorius1 Would love your product feedback as well, check it out on huddle01.com/ph you can also claim the PH discount
Hey Product Hunt 👋
I’m the person you see in the video, and if you haven’t watched it yet, now’s probably a good time.
Building Huddle01 Cloud has been one of the most exciting things I’ve worked on because it sits right at the intersection of infrastructure and AI. What AI changed for me as an engineer is not just speed, but the time and tools it gives me to understand systems more deeply, how traffic works, how packages work, and how different technologies fit together.
That’s a big reason why OpenClaw mattered to us. At Huddle01 Cloud, we’re building infrastructure like VMs, Kubernetes, and Load Balancers, but agents felt like where the world was clearly heading.
What got me hooked was seeing one of our engineers use OpenClaw for Polymarket trading and turn $1 into $17. I also gave it a shot and managed to turn $10 into $0 in about 30 minutes, so while that was humbling, it did confirm one thing: the tool is powerful, but the person using it still matters 😂
jokes aside, it showed me how powerful agents can be for repetitive, context-heavy work. We also saw how painful setup was, even for engineers, so we focused on making OpenClaw as close to one-click as possible.
Would love for you to try it out, push it hard, and tell us what you want us to improve.
@itsomg Turning $1 into $17 is impressive… turning $10 into $0 in 30 minutes is even more impressive in its own way 😂
Jokes aside, love the direction here. Making agents actually easy to deploy instead of another painful setup is a big win. Excited to see what people build with it!
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.
@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
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. 🚀
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?
@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.
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.
@mihir_kanzariya For Openclaw to work we need to keep docker container running, we don't shut them down