IrisGo, a startup backed by Andrew Ng, looks to become the AI desktop buddy you never knew you needed

Industry insiders say the next big thing in AI is “proactive” systems: agents that can anticipate a user’s needs — and fulfill them — before the user even knows what those needs are.

One startup that’s looking to make headway in this area is IrisGo. The company, which closed a $2.8 million seed round led by Andrew Ng’s AI Fund earlier this year, is building a desktop companion for PCs that can learn about a user’s daily workflows and then automate them with limited to no human prompting.

Iris was co-founded by Jeffrey Lai, a former Apple engineer who helped to build the Chinese language version of Siri, the company’s automated assistant. (Somewhat slyly, Iris is Siri spelled backwards.)

The core idea is simple: show Iris how to do something once, and it remembers that process for future automated use — no repeat instructions needed.

During a conversation with TechCrunch, Lai ran a demo, showing how Iris could learn to place a coffee order online. As I watched, Iris recorded the steps it took to select a latte from Philz Coffee (a popular Bay Area chain), fill out credit card information, and then hit purchase. Lai then asked Iris to repeat the order on its own; the agent dutifully complied.

Buying coffee, of course, is not really the point. Instead, the hope is that the system will automate a whole host of business-related tasks. Iris comes with a built-in “skills” library — things like email drafting, invoice processing, report building, document summarization, and many other ready-to-use automated workflows. At the same time, Iris learns from the user’s desktop behavior and automatically adds those tasks to its potential list of action items.

The application also includes a coding assistant — similar in concept to OpenAI’s Codex or Anthropic’s Claude Code — designed to assist developers as they go about their work.

“Our target audience is knowledge workers — white collar companies. There’s a lot of repetitive tasks that those workers do every day,” Lai said, noting that, despite the high-octane power of today’s frontier models, AI-assisted office work can still feel incredibly manual and repetitive. The goal, he said, is to move away from that and toward a more fully autonomous workflow, where the human works on high-level conceptual work while agentic systems take care of all the clerical work in the background.

A particularly appealing feature of Iris is that it is designed to process a lot of data on-device, giving it stronger privacy protections than other applications that rely heavily on the cloud. Lai says that the system is still a hybrid architecture — meaning that larger, more complex tasks are ultimately processed through the cloud, although the company promises that cloud processing “only occurs when explicitly authorized by the user and uses end-to-end encryption.”

Part of the strategy for scaling Iris has been to garner credibility through association with prominent figures and organizations. Support from Ng — notably a co-founder of the formative deep learning research team Google Brain — has helped. Lai managed to set up a meeting with Ng through a shared connection: both are alumni from Carnegie Mellon University. Lai and his co-founder demoed Iris during that meeting, and Ng’s AI Fund ultimately led the startup’s seed round. Nvidia and Google have also backed the company.

IrisGo recently launched the beta versions of its macOS and Windows apps, and the company is also currently pursuing deals with laptop companies to preinstall the app on new devices. It recently struck such a deal with Acer, and Lai said the hope is that the company can strike similar deals with other device makers soon.

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