Learn how Intel Optimized OpenClaw to Run More Securely and Cost Efficiently on Intel-based AI PCs

By Dr. Olena Zhu, Head of AI Solutions, Intel PC Ecosystem, and Adjunct Professor, Purdue University

Have you heard of OpenClaw?

This open-sourced, autonomous AI assistant has gained viral fame for its ability to reason, plan and perform tasks – all from your PC.

But as organizations and consumers evaluate how to deploy and scale OpenClaw – especially in sensitive enterprise settings where data security is a top priority – how can they ensure OpenClaw runs effectively while meeting the holy trinity of privacy, cost control and power efficiency demands?

This is where Intel can help.

Over the last few weeks, my team and I have been optimizing OpenClaw to address existing security and cost concerns by leveraging a hybrid execution approach.

Here are three reasons why OpenClaw runs best on Intel-based AI PCs:

#1: Hybrid execution protects privacy and balances real-world usability

Today, OpenClaw mostly operates using a cloud-only model.

Even though the core software is installed on your local device, your requests are still sent to AI models on the cloud.

My team and I believe there’s a more efficient path forward – one that’s based on a hybrid approach leveraging both cloud and local models.

We are optimizing OpenClaw on Intel-based AI PCs to use a hybrid execution approach designed to maximize privacy while preserving full agent functionality.

This means that tasks such as deep research on public information, which don’t require the use of sensitive data, can be run in the cloud, while sensitive data such as documents, meeting transcripts, and private files are processed locally.

Thanks to this hybrid execution approach, cloud services are only engaged when truly necessary for limited actions that you approve.

This approach limits the amount of data  transmitted to the cloud and allows organizations to keep sensitive context where it belongs – on local PCs, under their control, without restricting OpenClaw’s ability to interact with external systems.

By combining local and cloud intelligence, OpenClaw running on an Intel AI PC achieves a practical balance between data protection and real-world usability.

Here’s a quick demo that how OpenClaw can be configured to run on a hybrid agent architecture.

#2: Local-first processing reduces token costs

Reducing costs is another great reason for running OpenClaw on an Intel-based AI PC.

In short, doing so significantly reduces cloud token consumption, because large portions of agent reasoning and context processing are done locally.

For example, tasks such as document understanding, summarization, retrieval, and intermediate planning steps are handled on-device, minimizing the size and frequency of requests sent to cloud models.

As a result, organizations can scale OpenClaw usage more predictably, lowering per-task token costs while maintaining consistent performance across users and workflows.

#3: Low-power, always-on execution powered by Intel Series 3 PCs

OpenClaw runs more efficiently on Intel-based AI PCs thanks to new Intel® Core Ultra Series 3 platform processors (codenamed ‘Panther Lake’), which are designed to deliver high AI performance  at low power.

Series 3 supports large models exceeding 30 billion (30B) parameters when used in local and hybrid configurations.

This compute capability allows OpenClaw to keep key agent functions — such as context understanding, planning, memory management, and continuous monitoring, running locally on the PC, while maintaining a low power profile.

In day to day scenarios, this means your PC can remain in a standby state when you don’t need it, while still being responsive when you do.

As a result, Series 3–based AI PCs provide an ideal infrastructure for always-on, always-available agents: They combine the performance needed for advanced agentic reasoning with the power efficiency required for laptops and mobile form factors, enabling OpenClaw to act as a true 24×7 assistant without compromising battery life or thermal limits.

Hybrid AI is the future of agentic AI workloads: Meet Super Builder

OpenClaw may be the first viral AI agent to gain the world’s attention (it’s already earned well over 188,000 GitHub stars), but it won’t be the last.

As my team and I evaluated OpenClaw across a wide range of enterprise and consumer scenarios (including document and meeting analysis, task planning and coordinated actions with external tools), the process only strengthened my belief in charting the next path ahead for AI.

The evolution of AI is clear – users want AI to be local-first and want the control of AI and their data.

Hybrid AI is the path forward that fuses the best-of local with the advantages of cloud computing.  Future hybrid AI solutions will also evolve to the next level with deep collaboration between local and cloud models.

For example, cloud models can breakdown complex tasks and can guide local agents to process smaller workloads and process local data locally, ensuring private data stays private – with you in control, at all times.

This is why I’m excited about Intel’s forthcoming Super Builder releases. It will include the ability to tap into hybrid collaborative AI agents, using both cloud- and local-optimized AI processing.

Look out for more details coming soon.