From pre-orders to market entry, Rokid’s Taiwan campaign reflects how AI hardware is being introduced to consumers today.
Updated
January 8, 2026 6:30 PM
Rokid Glasses, a pair of AR glasses from Rokid. PHOTO: ROKID
Rokid has reached a significant crowdfunding milestone in Taiwan. Its Rokid Glasses campaign surpassed NT$62 million in pre-order funding on zeczec, Taiwan’s creative-oriented crowdfunding platform. The campaign ranked No. 1 across all categories on the platform in 2025 and entered the Top 10 funded campaigns in zeczec’s history, setting new records for AI and XR-related projects.
The campaign launched on October 28 and became one of the platform’s most prominent technology initiatives of the year. According to the company, the outcome followed growing visibility for Rokid Glasses after product showcases in New York, Berlin, Singapore and Paris, positioning the Taiwan campaign within a broader international rollout.
The crowdfunding achievement coincided with Rokid’s official market entry in Taiwan. On December 10, the company debuted Rokid Glasses locally, introducing the product to media, partners and early users in the region. The Taiwan launch mirrored earlier international events and connected the online crowdfunding campaign with a physical market presence.
Rokid Glasses combine augmented reality displays with built-in AI functions, including real-time multilingual translation, live transcription, navigation, object recognition and voice assistance. These capabilities were central to how the product was presented during both the crowdfunding campaign and the Taiwan launch, without framing the project as a traditional consumer electronics release.
The Taiwan campaign builds on Rokid’s prior crowdfunding history. The company previously raised more than US$4 million on Kickstarter, where Rokid Glasses became the highest-funded XR wearable project on the platform. The zeczec campaign extends that track record into one of Asia’s most established consumer electronics markets.
“Taiwan has one of the world's most mature and discerning consumer electronics markets”, said Said Justo Chang, Head of Global Channels at Rokid. “Reaching the top of Taiwan's crowdfunding platform is a great commercial achievement. We are excited to finally introduce Rokid Glasses to Taiwan”.
More broadly, the campaign highlights how crowdfunding platforms continue to function as launch and distribution channels for emerging AI and XR hardware. In Rokid’s case, product rollout, market entry and public participation converged within a single campaign, marking a notable moment for AI-enabled wearables in Taiwan’s technology landscape.
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A look at how motivation, not metrics, is becoming the real frontier in fitness tech
Updated
January 23, 2026 10:43 AM
A group of people running together. PHOTO: FREEPIK
Most running apps focus on measurement. Distance, pace, heart rate, badges. They record activity well, but struggle to help users maintain consistency over time. As a result, many people track diligently at first, then gradually disengage.
That drop-off has pushed developers to rethink what fitness technology is actually for. Instead of just documenting activity, some platforms are now trying to influence behaviour itself. Paceful, an AI-powered running platform developed by SportsTech startup xCREW, is part of that shift — not by adding more metrics, but by focusing on how people stay consistent. The platform is built on a simple behavioural insight: most people don’t stop exercising because they don’t care about health. They stop because routines are fragile. Miss a few days and the habit collapses. Technology that focuses only on performance metrics doesn’t solve that. Systems that reinforce consistency, belonging and feedback loops might.
Instead of treating running as a solo, data-driven task, Paceful is built around two ideas: behavioural incentives and social alignment. The system turns real-world running activity into tangible rewards and it uses AI to connect runners to people, clubs and challenges that fit how and where they actually run.
At the technical level, Paceful connects with existing fitness ecosystems. Users can import workout data from platforms like Apple Health and Strava rather than starting from scratch. Once inside the system, AI models analyse pace, frequency, location and participation patterns. That data is used to recommend running partners, clubs and group challenges that match each runner’s habits and context.
What makes this approach different is not the tracking itself, but what the platform does with the data it collects. Running distance and consistency become inputs for a reward system that offers physical-world incentives, such as gear, race entries or gift cards. The idea is to link effort to something concrete, rather than abstract. The company also built the system around community logic rather than individual competition. Even solo runners are placed into challenge formats designed to simulate the motivation of a group. In practice, that means users feel part of a shared structure even when running alone.
During a six-month beta phase in the US, xCREW tested Paceful with more than 4,000 running clubs and around 50,000 runners. According to the company, users increased their running frequency significantly and weekly retention remained unusually high for a fitness platform. One beta tester summed it up this way: “Strava just logs records, but Paceful rewards you for every run, which is a completely different motivation”.
The company has raised seed funding and plans to expand the platform beyond running, walking, trekking, cycling and swimming. Instead of asking how accurately technology can measure the body, platforms like Paceful are asking a different question: how technology might influence everyday behaviour. Not by adding more data, but by shaping the conditions around effort, feedback and social connection.
As AI becomes more common in consumer products, its real impact may depend less on how advanced the models are and more on what they are applied to. In this case, the focus isn’t speed or performance — it’s consistency. And whether systems like this can meaningfully support it over time.