Launched this week
ClawTeams
The first goal-driven, proactive AI team for e-commerce
1.2K followers
The first goal-driven, proactive AI team for e-commerce
1.2K followers
ClawTeams is an AI employee platform for e-commerce sellers. Instead of hiring specialists—or doing everything yourself—you get a coordinated AI team that thinks, plans, and executes like real employees. One goal. One team. Zero micromanagement. Tell your team lead what you want—"Increase Q4 revenue by 20%"—and they break it down, assign specialists, and run the plan. You get updates in Slack or Discord. High-stakes decisions wait for your approval. Everything else just happens.
Which integrations are available today beyond Slack, and is Microsoft Teams support already production-ready?
ClawTeams
@ea_z slack/Telegram/Lark/Wecom/Dingtalk ready
Teams/discord coming soon, hopefully ready by next week
What is actually highlighted for me to approve when the lead of the artificial intelligence team breaks down a goal such as increase fourth quarter revenue by 20% into specific actions, and does this depend on me or is it set up by the platform itself?
ClawTeams
@saksham_salvi Great question! The short answer: you control the principles, and ClawTeams designs the breakdown. Our goal is to autonomously generate and execute solutions based directly on your needs and goals. But we recognize that different industries, companies, and users often approach even the same problem very differently, so the agents don't rely on hard-coded decomposition rules baked into the platform. Instead, they work from a small set of preset principles/rules, and then flexibly design and break down the solution based on the specific context of your interactions with them. That's where human-in-the-loop comes in: you control those few preset principles/rules, while the product handles the autonomous design and decomposition. And often the agents will return multiple execution plans for you to decide between, or ask you to sign off before adopting a specific plan.
Congrats on the launch! When it comes to spending real money, like reordering inventory or bumping ad budget, where's the line between "just handle it" and "wait for my approval"? Is that a fixed threshold or something you tune per store?
ClawTeams
@irahimiam Great question! Every business tends to want to set these rules differently, so we've chosen to leave that flexibility to the user rather than hard-coding a fixed threshold. At the org/admin level, you can set unified guardrails that govern all agents across the organization. Then, individual users can set their own rules for their specific agent. The one constraint is that lower-level rules can't conflict with (or override) the higher-level org rules. So you get both centralized control and per-store tuning.
How does it work under the hood? Do you have your own knowledge base covering different e-commerce industries? In other words, what guarantees do you have that the AI won't generate incorrect or harmful recommendations?
ClawTeams
@natalia_iankovych Really important question, thank you. A few parts to it:
Under the hood: Your AI Team Lead breaks a goal into a plan and delegates to specialist agents. Rather than hard-coding one "correct" playbook, the agents design and decompose solutions based on the specific context of your business and your ongoing interactions — grounded in your own data (catalog, sales, past decisions) plus a small set of preset principles you control.
On the knowledge base: We don't pretend to be an omniscient oracle for every industry. Instead of relying purely on a static, baked-in knowledge base, the agents work from your business context and connected data(that you shared), so recommendations are grounded in your reality rather than generic assumptions.
On guarantees / avoiding harmful output: We're honest that no AI can guarantee zero errors — so the safeguards are structural rather than a promise of perfection. High-stakes actions wait for your explicit sign-off (human-in-the-loop), agents often return multiple plans for you to choose between rather than executing blindly, and every step is transparent and traceable with updates in Slack/Discord. The aim is to keep you in control of consequential decisions while automating the routine execution.
Happy to go deeper on any of these!
Love the concept of treating AI agents like actual team members. One thing I'd find super useful is a simple performance dashboard per specialist showing what they shipped, time saved, and cost vs hiring a human for the same task, so I can actually measure ROI over time.
ClawTeams
@tahazgnkdof Thanks so much, Taha — really glad the "AI agents as teammates" framing resonates! Good news on the ROI front: we already have a budget management function that lets you track and manage your agent team's spend, so you can keep an eye on cost as you go. A fuller per-specialist view (what each agent shipped + time saved side by side) is exactly the direction we want to take it further. Would love to hear which metrics matter most to you!
Would love to see a quick weekly recap card in Slack showing what the team actually did and what it cost in API credits, so I can tell at a glance whether I'm getting real value or just noise.
Ada.im
Are users able to bring their own models or choose different models for different AI roles?
Ada.im