GoKawiilIndustry 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.
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