When I first heard about AI assistants that could live inside your messaging apps, I was skeptical. Another chatbot? We've all seen those. But when I got my hands on OpenClaw and started building what we now call Clawd Bot at Harshith Ventures, everything changed.
What is OpenClaw?
OpenClaw is an open-source framework that lets you deploy AI agents as always-on assistants across multiple messaging platforms. Unlike simple chatbots that respond to commands, OpenClaw agents are proactive. They can check your calendar, read your emails, search the web, execute code, and most importantly, they remember context across conversations.
The core idea is simple but powerful: give a large language model (like Claude or GPT) access to tools, memory, and messaging channels, and let it act as a genuine digital teammate rather than a glorified search bar.
Why We Built Clawd Bot
At Harshith Ventures, our team communicates across Slack, Telegram, and WhatsApp. Messages get lost. Action items fall through the cracks. Someone asks a question in Telegram, and the answer is buried in a Slack thread from two weeks ago.
We needed something that could bridge all three platforms, maintain context, and actually do things, not just answer questions.
The Setup
Setting up OpenClaw was surprisingly straightforward. The framework runs as a Node.js service on any Linux machine. Here's what the architecture looks like:
1. **Gateway Server** runs on our infrastructure (a simple Azure VM)
2. **Channel Plugins** connect to Slack, Telegram, and WhatsApp simultaneously
3. **Claude Opus 4.6** serves as the underlying language model with 1M token context
4. **Skill System** lets you add capabilities like GitHub integration, Google Workspace, web search, and custom tools
5. **Memory System** gives the bot persistent memory across sessions using markdown files
The beauty is that a single bot instance handles all three channels. When someone asks a question on WhatsApp, Clawd Bot has the same context and memory as when it's operating in Slack.
What Clawd Bot Actually Does
Here's a typical day for our AI assistant:
Morning: Checks unread emails and flags anything urgent in our #notifications Slack channel. Summarizes the calendar for the day.
During work: Answers questions from team members across all three platforms. If someone in Telegram asks about a project deadline, it can pull that information from our Slack channels or previous conversations.
Proactive checks: Every few hours, it does a sweep of emails, calendar events, and notifications. If something needs attention, it reaches out.
Operations: It can create GitHub issues, search the web for research, draft messages, and even generate reports.
Lessons Learned
1. Memory is everything. The difference between a useful AI assistant and an annoying chatbot is memory. OpenClaw's memory system (markdown files that persist across sessions) means Clawd Bot actually learns our preferences and context over time.
2. Multi-channel is a game changer. Having one assistant that works across Slack, Telegram, and WhatsApp eliminates the "which app was that in?" problem entirely.
3. Proactivity beats reactivity. The heartbeat system in OpenClaw lets the bot periodically check things and reach out when something needs attention. This is far more valuable than waiting to be asked.
4. Start simple, add complexity. We started with just Slack integration and basic Q&A. Over time, we added Telegram, WhatsApp, email checking, calendar integration, and custom skills. Trying to do everything at once would have been overwhelming.
The Impact
After two months with Clawd Bot, our team communication is genuinely better. Response times are faster because someone (or something) is always available. Nothing falls through the cracks because the bot maintains context across all channels. And the operational tasks that used to eat up hours each week are now handled automatically.
Is it perfect? No. Sometimes it misunderstands context. Occasionally it's too eager to help when silence would be better. But it learns, and it gets better every week.
Getting Started
If you're interested in building something similar, OpenClaw is open source and available on GitHub. The documentation is solid, and the community on Discord is active and helpful. You don't need a massive infrastructure setup; a basic VM with Node.js is enough to get started.
The future of team productivity isn't another project management tool. It's an AI teammate that actually understands your workflow and helps without being asked.