Alibaba Open-Sources HiClaw and CoPaw: AI Agents That Don't Need Powerful Servers

Running an AI agent on a regular computer without a powerful graphics processing unit (GPU) or cloud infrastructure sounds like something that's «theoretically possible, but not very practical.» Nevertheless, this is precisely the direction Alibaba is heading by open-sourcing two of its developments: HiClaw and CoPaw.

What are HiClaw and CoPaw AI agents for?

What Are These Agents and What Are They For?

AI agents are programs that don't just answer questions but also perform tasks: clicking buttons, filling out forms, switching between applications, and reading the screen. Simply put, they do what a person typically does on a computer, but automatically.

Most such agents require substantial resources: they need to constantly «see» the screen, understand what's happening on it, and make decisions. This involves a large amount of RAM and significant computing power – especially if the agent operates in real-time.

HiClaw and CoPaw emerged as an attempt to break this dependency. Their main feature is a drastic reduction in memory consumption while maintaining practical functionality.

How HiClaw and CoPaw AI agents work together

How They Divide the Work

These two tools work in tandem but perform different tasks.

HiClaw is responsible for perception: it «looks» at the screen and analyzes what is being displayed. It's designed to process only the part of the screen that is currently needed, rather than loading the entire interface into memory. This provides the primary resource savings.

CoPaw is the executive part of the duo. It makes decisions and manages actions: what to click, where to navigate, what to fill in. Because HiClaw provides it with already «pre-digested» information, CoPaw isn't overloaded with unnecessary data.

To draw an analogy: HiClaw is the eyes, trained to look only where necessary, while CoPaw is the hands, acting on what is seen.

Why low memory AI agents are important

Why «Low Memory» Actually Matters

It might seem that saving memory is just a technical detail of interest only to developers. But there's something more significant behind it.

Most powerful AI agents today reside in the cloud. This means user data – screen captures, action history, task context – is sent to third-party servers. For corporate use, this is often unacceptable due to confidentiality concerns, internal security policies, and regulatory restrictions.

Lightweight agents capable of running locally – that is, directly on the user's device – eliminate this problem. The data goes nowhere. Everything happens internally.

Furthermore, local operation means no network-related delays and independence from internet connection quality. For automating workflows, especially routine office tasks, this is a tangible advantage.

Open source strategy for Alibaba AI agents

Open Source Is a Whole Other Story

Alibaba didn't just develop and use these tools internally – it open-sourced them. This means any developer can take HiClaw and CoPaw, study how they work, modify them for their own needs, or integrate them into their own products.

In the AI industry, open source is currently not just a gesture of goodwill. It's a way to quickly get feedback from the community, attract developers to contribute to the tool's growth, and secure a position in the growing competition between open and closed ecosystems.

For small teams and independent developers, this opens up the opportunity to create agent-based solutions without having to build everything from scratch or pay for cloud computing power.

Limitations of HiClaw and CoPaw AI agents

What's Left Out of the Picture

Reduced memory consumption is good news, but every compromise comes at a price. It's not yet entirely clear how well the HiClaw + CoPaw duo handles complex, multi-step tasks compared to more resource-intensive solutions. Lightweightness and versatility don't always go hand in hand.

The question also remains open as to how easy it will be to integrate these agents into real-world work environments – with non-standard interfaces, complex applications, and atypical use cases. This will become clearer as the community begins to work with the code.

Nevertheless, the trajectory is clear: AI agents are becoming more lightweight, more accessible, and less dependent on cloud infrastructure. HiClaw and CoPaw are another step in this direction.