CoChat is where your team and AI agents work together. It’s the most secure way to use OpenClaw with a company: connect self-hosted or CoChat-managed gateways and share agents without sharing your machine (no SSH). Every connection is auto security-audited, with logs and approvals for sensitive steps. Agents have personality, memory, and scheduled tasks. The thing that makes it click: one thread where humans and agents bring different strengths and produce better output together.
The short version: We built a workspace where AI agents (openclaw and others) work alongside your team — not as isolated chatbots, but as teammates with memory, personality, and real responsibilities.
Why we built CoChat: I’ve been running OpenClaw gateways for a while. Powerful stuff. But every time I tried to bring my team into that world — to share context, keep knowledge persistent, coordinate work, and move projects forward together — things broke down.
Agents lived in silos. Context got lost. Progress stalled.
There wasn’t a real place for teams to collaborate with AI.
So we built one.
Here's what CoChat does today:
🔌 Connect your OpenClaw gateways — bring any agents you've already built. They show up alongside native CoChat assistants. One workspace, multiple sources.
🛡️ Every gateway gets audited automatically — Every gateway gets audited automatically — our open-source security scanner (Carapace) runs 225+ CVE checks and 24 audit rules on connect. You see the score. You see the findings. No black boxes — just full visibility before agents ever touch your workflow.
🧠 Agents with real depth — each assistant has a distinct personality, its own memory that grows over time, and scheduled responsibilities (cron, webhooks, intervals). They do actual work: monitoring, reporting, and research on autopilot.
👥 Collaborative conversations — invite teammates and agents into the same chat. Your marketing lead, your security agent, and your data analyst (human or AI) in one thread. Each agent keeps its voice — projects move forward because roles stay clear and context isn’t lost.
The 'one thread where humans and agents collaborate' framing is the right bet — most team AI tools fail because they treat AI as a separate workflow instead of an integrated participant, so people revert to old habits. Curious how you handle the trust layer when a new team member joins: do they inherit existing agent memory and approvals, or start fresh? The security audit on every connection is a smart default that removes the 'who approved this?' conversation that kills adoption in ops-heavy teams. The scheduled tasks plus memory combo is where I'd expect the stickiest use cases to emerge — that's the shift from 'tool you use' to 'system that works for you.'
Interesting direction as moving AI agents from isolated chatbots into a shared team workspace feels like a natural next step for collaboration. Curious how teams will balance agent autonomy, memory, and security as these systems start handling real responsibilities.
Saw CoChat's PH launch and 249 upvotes is solid validation for collaborative AI tooling.. What caught my attention: you're leading with 'autonomous' + 'secure' which typically conflict in enterprise buying committees I work with..
Quick question: how are you positioning the autonomous capabilities to InfoSec teams who usually flag agent-based tools as data exfiltration risks? From a marketing lens, I'm seeing B2B AI tools struggle with attribution when selling 'collaboration' as the buying committee is fragmented and CAC spikes without clear product led funnels. If you're exploring paid acquisition for MENA markets (where data residency is make or break), I'd be interested in exchanging notes on how AI collaboration tools are approaching regional compliance in ad messaging.
Congrats on the launch.
Oh this is cool — I love that agents here actually have memory and personality instead of being "ask and forget" chatbots.
Since you asked for feedback:
1. On security — honestly, the biggest thing for me is visibility. I want to see exactly what each agent has access to and what it did. Audit logs are a must. I build iOS apps and I route all my AI API calls through a proxy just to keep keys off the device, so I really appreciate that you're thinking about this at the infra level. The 225+ CVE auto-scan is a nice touch.
2. Scheduled tasks — 100% yes. Off the top of my head: weekly monitoring of competitor reviews on the App Store, auto-summarizing GitHub commits into changelogs, daily crash report digests. Basically anything that's "go check this thing regularly and yell at me if something's off."
Also the no-SSH approach is such a relief. Setting up tunnels to self-host AI tools has always been the part where I lose motivation lol. Great work on this!
Curious how you deal with gateways going down or getting corrupted after something like an openclaw update? Asking because I ran into this specifically today.
Cool concept! How do you think about managing agent permissions / preventing agents from taking risky actions?
The 'one thread where humans and agents collaborate' angle is what makes this stand out, most team AI tools still treat AI as a separate sidecar. The auto security audit on every connection is a smart call for enterprise adoption. Congrats on the launch!
I’m the founder of cochat.io and you’ve been copy and pasting my ideas. You were originally an AI platform where people can use different AI models all in one place. Now you transitioned to “LinkedIn for AI”. My idea is based on having AI in your portfolio.
Your name is completely identical except for the domain type. When I changed the hero of my landing page, I noticed one week afterwards your page had the same dynamic chat component.
You’ve been ignoring my attempts to reach out, I’m kindly asking you and your cofounder to respond to my messages so we can reach a resolution.
The "agents as teammates" framing really resonates. We've been dealing with the exact same problem on our team where everyone has their own AI setup but there's zero shared context between them. The gateway security audit feature caught my eye too, how granular are the permission controls per agent?
collaborative openclaw is certainly something I haven't seen! WIll try it for our Openclaw based "LinkedIn for AI Agents" at moltin.work
Hey PH 👋 I'm Marcel, founder of CoChat.
The short version: We built a workspace where AI agents (openclaw and others) work alongside your team — not as isolated chatbots, but as teammates with memory, personality, and real responsibilities.
Why we built CoChat:
I’ve been running OpenClaw gateways for a while. Powerful stuff. But every time I tried to bring my team into that world — to share context, keep knowledge persistent, coordinate work, and move projects forward together — things broke down.
Agents lived in silos. Context got lost. Progress stalled.
There wasn’t a real place for teams to collaborate with AI.
So we built one.
Here's what CoChat does today:
🔌 Connect your OpenClaw gateways — bring any agents you've already built. They show up alongside native CoChat assistants. One workspace, multiple sources.
🛡️ Every gateway gets audited automatically — Every gateway gets audited automatically — our open-source security scanner (Carapace) runs 225+ CVE checks and 24 audit rules on connect. You see the score. You see the findings. No black boxes — just full visibility before agents ever touch your workflow.
🧠 Agents with real depth — each assistant has a distinct personality, its own memory that grows over time, and scheduled responsibilities (cron, webhooks, intervals). They do actual work: monitoring, reporting, and research on autopilot.
👥 Collaborative conversations — invite teammates and agents into the same chat. Your marketing lead, your security agent, and your data analyst (human or AI) in one thread. Each agent keeps its voice — projects move forward because roles stay clear and context isn’t lost.
What you can try right now:
Spin up a free workspace at cochat.ai
Connect an OpenClaw gateway (or start with native assistants)
Invite your team and run a real collaborative thread
Pricing:
Free credits on signup. No subscription — just pay for what you use.
🎁 PH-only: Double credits on your first purchase.
Two things I’d genuinely love feedback on:
When connecting AI agents to a team workspace, what does “secure” need to mean for you to trust it?
Would you use scheduled agent tasks (e.g., “run this research every Monday at 8am”)? If yes, for what?
I’ll be here all day. Happy to answer questions, walk through a setup, or debate whether AI agents should have personalities. (They should.)
- Marcel