an experiment on giving your @openclaw bot a real crm to operate on.
for a while now, while building plugins and skills, we kept running into the same practical limitation.
when we needed to organize leads, track conversations, assign follow-ups, move deals across stages, or simply understand where things stood, we were forced to rely on external tools that weren’t built for agents.
they solve the problem for humans, but they don’t map cleanly to how agents execute workflows.
so we built the crm layer we wanted to use ourselves.
a lightweight, open system that behaves like a traditional crm, but is designed so your @openclaw agent can operate it directly via api.
introducing OpenClaw CRM
→ generate a skill file tailored to your instance
→ plug it into your OpenClaw config
→ your agent can create and update contacts, manage deals, move pipeline stages, assign tasks, attach notes, and query structured records as part of its workflow
→ the solution also includes a built-in ai layer.
while connected to your OpenClaw bot, it can analyze activity, surface context, and act on structured data instead of just storing it.
under the hood:
→ 19 structured endpoint categories covering core crm logic
→ 40+ rest endpoints across contacts, deals, tasks, notes, stages
→ fully self hostable, so you control the data and infrastructure
we’re already running it inside our own processes, and we’ll keep refining it as those processes evolve.
At DoloresLab, we're pushing AI-Linux integration to the next level! Our AI not only interacts with Linux tools but learns from them in real-time, enhancing automation, cybersecurity, and system management. We are in beta vrs more is coming—stay tuned!
#AI#Linux#CyberSecurity
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