Lingverse Raises $29 Million to Develop iKairos, an AI Wearable Inspired by Jibo

Singapore-based AI hardware company Lingverse has raised US$29 million in Pre-A funding to develop iKairos, a modular wearable designed to understand both its user and the surrounding environment.

The company describes iKairos as a continuation of the vision behind Jibo, the expressive social robot that attracted widespread attention following its 2014 crowdfunding campaign. Rather than recreating Jibo as another stationary home robot, Lingverse is adapting the concept for an era of multimodal AI, wearable cameras, and context-aware assistants.

Lingverse has not disclosed the participating investors, its valuation, or the specific financial terms of the round. The funding will support the development and planned commercialization of iKairos, with preorders expected to begin in the third quarter of 2026.

Moving the Social Robot Beyond the Desktop

Jibo was designed as a social presence for the home, using cameras, microphones, facial recognition, and an animated display to communicate with people. Its expressive movements helped distinguish it from the voice assistants and smart speakers emerging at the time.

The robot was included in TIME’s Best Inventions of 2017, but its commercial life proved short. Jibo Inc. ceased operations in 2018, and users received a farewell message the following year warning that the servers supporting many of its capabilities would soon be turned off.

That ending became an enduring example of both the emotional potential and commercial risks associated with social robotics. Lingverse is revisiting the underlying idea, but with a different form factor and a more ambitious approach to perception.

Where Jibo remained in one location, iKairos is being developed as a modular device that can operate as either a wearable or a desktop companion. The design preserves an expressive face inspired by Jibo while allowing the device to accompany its user throughout the day.

A Wearable That Looks in Two Directions

Most camera-equipped wearables observe the environment from the wearer’s point of view. They can identify objects, answer questions about what the user sees, capture photos, or provide information about nearby places.

Lingverse argues that this perspective is only part of the context an AI assistant needs.

iKairos is designed to shift its gaze between the user and the outside world. One perspective can observe the wearer’s expressions, activities, and behavior, while the other can interpret objects, people, and events occurring around them.

By combining these perspectives over time, Lingverse intends for iKairos to build a more detailed understanding of the user’s circumstances. Rather than waiting for a direct prompt, the system could eventually determine when a reminder, question, or suggestion may be useful.

The company refers to this role as an “AI guardian,” although the initial release does not specify the full range of tasks available at launch. Details including battery life, weight, pricing, supported AI models, connectivity, and third-party integrations have also not yet been announced.

From Prompt-Based Assistance to Persistent Context

The larger technical bet behind iKairos is that the next generation of personal AI devices will need to understand more than isolated commands.

Large language models can respond to detailed prompts, but they generally lack direct knowledge of what a person has been doing throughout the day. Wearables can potentially fill that gap by collecting visual, audio, location, and behavioral context before passing relevant information to an AI system.

This approach could enable an assistant to recognize that a user has forgotten an item, is preparing for a scheduled activity, or may need information connected to what is happening nearby. It could also allow the system to personalize its behavior based on routines rather than relying exclusively on manually configured preferences.

However, persistent observation introduces difficult questions involving privacy, social acceptance, data ownership, and the accuracy of AI-generated interventions. A device that attempts to anticipate a person’s needs must distinguish between genuinely helpful moments and situations where interruption would be intrusive.

Privacy Controls Built Into the Device

Lingverse says iKairos is being developed with privacy protections at both the hardware and system levels.

The device includes a physical camera shutter that users can close to block visual observation. Lingverse also says personal data will either be processed locally or encrypted while being transmitted, and that user data will not be used to train the underlying AI models.

These commitments could become an important part of the product’s positioning, particularly because iKairos is intended to observe its wearer for extended periods. The effectiveness of those protections will ultimately depend on the product’s technical architecture, default settings, retention policies, and the amount of processing that can occur on the device.

Lingverse has not yet released detailed technical documentation explaining which features operate locally, which require cloud services, or how users will be able to review and delete the information collected about them.

Jiawei Gu’s Path Through Human-Computer Interaction

Lingverse founder and CEO Jiawei Gu has spent much of his career working on systems that combine computer vision, AI, and physical devices.

Gu previously worked at Microsoft (MSFT ) Research and later led human-computer interaction initiatives at Baidu’s Institute of Deep Learning. His work included BaiduEye, an early wearable computing project, and DuLight, a system that used cameras and deep learning to help visually impaired users recognize objects and written information.

Before founding Lingverse, Gu served on Jibo’s board and created Luka, an owl-shaped reading companion that recognizes physical picture books and reads them aloud to children. Luka’s current platform says the device can recognize more than 20,000 English picture books and 70,000 Chinese titles.

iKairos brings those strands together. It combines the expressive qualities associated with social robots, the portability of wearable hardware, and the visual understanding made possible by modern multimodal AI.

Future Implications for Context-Aware AI Wearables

Devices such as iKairos point toward a shift from prompt-based assistants to AI systems that continuously interpret their users and surroundings. If this approach proves reliable, future wearables could provide assistance based on ongoing context rather than waiting for explicit instructions, potentially changing how people interact with calendars, communications, health tools, and connected devices.

That shift would also introduce significant privacy and governance challenges. A wearable that observes both the user and the surrounding environment may capture information about bystanders who have not consented to being recorded. Physical camera controls and on-device processing could reduce some risks, but manufacturers will still need to be transparent about what is collected, how long it is retained, and which features depend on cloud infrastructure.

The category will ultimately depend on whether proactive assistance is consistently useful rather than intrusive. Context-aware AI systems will need to understand when to intervene, when to remain silent, and how to communicate uncertainty when they misinterpret a situation. The companies that solve those problems may help establish a new form of ambient computing, while those that fail could reinforce existing concerns about surveillance, unreliable automation, and the long-term viability of cloud-dependent hardware.