OpenClaw is the most popular open source AI agent on the planet. Running it yourself? That's the hard part. KiloClaw is a fully managed, hosted version of OpenClaw. We handle the infrastructure, security, updates, and monitoring so you can focus on what your agent actually does - not keeping it alive.
Humans in the Loop
If you've played around with @OpenClaw, you know the drill: 30-60 minutes of SSH, environment config, dependency juggling, unexpected crashes, and manual updates... It's fun at first, then we move on.
@KiloClaw fixes this:
One-click deploy
50+ chat platforms
500+ AI models via @Kilo Code
OpenClaw is awesome. KiloClaw makes it accessible to everyone: kilo.ai/kiloclaw - Thank you, ?makers
@fmerian I had big wall to make open claw system, although I think I need to use. KiloClaw will be my best solution, thank you!
Humans in the Loop
@chunhee awesome! s/o to @pandemicsyn and the @Kilo Code team - keep 'em posted in their Discord: kilo.ai/discord
Skillkit
Humans in the Loop
awesome collection, Rohit - thanks for featuring @KiloClaw and looking forward to contributing to it!
Sleek Pay
@fmerian so excited to try this! Kilo + OpenClaw = safe + simple deployment
Humans in the Loop
exactly! let us know what you think on Discord: kilo.ai/discord
The move from self-hosted to managed infra follows the same arc as databases a decade ago — same privacy debate, same setup/maintenance tax, same eventual outcome. Most teams traded local control for managed convenience once the offering was mature enough. Curious if dedicated instances for teams with stricter data requirements are on the roadmap?
Kilo Code
@giammbo currently this is only on our personal plans, so we plan to add it to our Teams and Enterprise plans with exactly what I think you're thinking there - the ability for organizations to deploy these tools in a way that they can understand and control while still giving their teams the power of these new tools
@realolearycrew That makes sense as a sequencing decision — personal plans give you the feedback loop to harden the deployment model before adding org-level controls. Glad to hear enterprise is on the roadmap.
Interesting launch — but I think there’s an important elephant in the room here.
Tools like OpenClaw and other “personal AI assistants” were compelling largely because they aimed to keep computation and data local. Once you move that into a hosted/cloud environment, you reintroduce the exact risk many users were trying to avoid: PII, system context, files, and behavioral data flowing to third-party infrastructure.
If sensitive prompts, logs, or system-level interactions are still traversing cloud endpoints, doesn’t that fundamentally defeat the purpose of a personal/local-first AI assistant?
I’d really like to see clear documentation around:
– What data leaves the user’s machine
– What is stored, for how long
– Whether any telemetry or logs are retained
– How you prevent unintended data exfiltration
Convenience is great — but privacy is the whole value proposition here. Without strong guarantees, this just becomes another cloud AI wrapper.
Kilo Code
@shivansh_anand_srivastava1 Totally agree! And we're working on a security white paper to bring clarity here. Do you think that would help? As a preview I've attached the current draft's outline below.
I also wrote about how I think about separation for my OWN OpenClaw instance here: https://blog.kilo.ai/p/open-claw-is-my-intern?utm_source=publication-search. Would love to know your thoughts on that.
@realolearycrew Appreciate the response, Brendan - and especially the transparency around working on a security white paper. That’s exactly the kind of clarity this space needs.
I also liked your “OpenClaw as my intern” framing. Treating the agent as a scoped contributor with defined boundaries, review loops, and separation of concerns is a much more mature way to think about agent autonomy than just giving it unrestricted access. That mindset - capability with deliberate containment - is what will ultimately build trust in hosted AI systems.
The capability vs. privacy trade-off is very real. If the white paper clearly maps data flow boundaries, retention policies, isolation guarantees, and exfiltration controls, I think it would set a strong standard for the ecosystem.
On a related note, I saw a tool created for same problem space - declaw, launched on Product Hunt today only. Haven’t tried it yet, but the premise of adding a local security layer in front of agents to filter outbound traffic seems interesting.
Humans in the Loop
thank you for the feedback!!
@shivansh_anand_srivastava1 This is a really important point.
A lot of AI tooling conversations focus on convenience first and infrastructure second — but once sensitive workflows are involved, architecture matters more than UX.
We’ve seen a similar dynamic in fundraising infrastructure. Founders optimise for speed (more outreach, more automation), but the real risk sits in how capital exposure, data rooms, and investor interaction are structured underneath.
Clarity around:
– What data leaves the system
– Where it’s processed
– How logs are handled
– What is structurally retained
…is what separates “wrapper convenience” from institutional infrastructure.
Appreciate you raising this — these are the right questions for any platform that touches high-signal workflows.
Humans in the Loop
great feedback. the team is working on a security white paper to bring clarity here.
stay tuned!
The gap between "this open source tool is incredible" and "I actually run it in production" is where most developer tools lose people. SSH, environment config, dependency juggling ... that's not the work anyone signed up for.
I've been through this exact cycle building my own infrastructure. You spend a weekend getting something deployed, it works great, then three weeks later a dependency update breaks it silently and you're back to debugging infra instead of building product. Curious about the 500+ AI models integration. How are you handling model-specific quirks in tool calling and context window management across that many providers? That's always been one of the trickiest parts in my experience.
Humans in the Loop
Spot on!
@KiloClaw is powered by @Kilo Code, an open-source product used 1.5M developers worldwide. You can learn more about it here: kilo.ai/gateway
Hope it helps!
Calling Clones
SO I could use this as the brain on my raspberry pi voice assistant at home????? Im not a developer, is it easy? haha. ( dont trust chatgpt opinion on this)
Kilo Code
@javierfandos No the idea of this is to NOT have to bring your own hardware...so this runs OpenClaw in our cloud not on your hardware.
Calling Clones
@realolearycrew I meant Raspberry Pi voice interface and then KiloClaw as cloud cognition.
This is still to hard to set up for me I guess.. I might have to wait few more months until one-click solution comes.
Excellent one-click install of OpenClaw. Everything works beautifully. I was able to log in and chat with the OpenClaw bot.
The challenge here is that there is no terminal access, so we don't have any control over the instance. If you guys know, let me know. I tried putting the Telegram bot token, and it's asking to restart; then I restarted multiple times. It never worked. Finally, the bot recognizes in the chat window that Telegram is activated, but still, when I messaged from Telegram, the pairing is not happening and the pairing request keeps spinning. Nothing is happening there.
Can you guys troubleshoot this pairing with Telegram? I'm sure Discord and Slack also have similar problems. Better to give us the terminal access so we can troubleshoot this.
Humans in the Loop
good feedback cc: @pandemicsyn and @realolearycrew for the record
Triforce Todos
Kilo Code
@abod_rehman thanks!
Humans in the Loop
framing this! Let's spread the word on X