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.
Bringing teams and AI agents together in a secure shared workspace is a strong concept. How are companies thinking about scaling this across different departments?
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