A Hong Kong pilot explores how creator-led distribution could reshape livestreaming for global competitions
Updated
April 8, 2026 5:28 PM
A dance crew performs in sync on stage at World of Dance under spotlights. PHOTO: WORLD OF DANCE HONG KONG
On January 22, 2026, World of Dance Hong Kong became the first global event to pilot Mitico’s community-based livestreaming model. The idea is simple: rethink how live competitions are shared in a digital-first world.
Instead of relying on a single official broadcast, the event was produced as one centralised live feed. It was then distributed across multiple creators and influencers, each hosting the stream for their own audience.
This gave creators room to add their own commentary, adapt the language and bring in cultural context that suited their communities, while the production remained consistent behind the scenes.
“Dance is a universal language”, said David Gonzalez, President of World of Dance. “Our collaboration with Mitico to produce an international, creator-led livestream in Hong Kong allowed a regional competition to reach a global audience. With personalised commentary from hosts in different languages, we can begin to see how regional events may connect through global communities”. This approach points to a shift away from traditional broadcaster-led distribution and toward creator-led amplification.
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Mitico’s approach begins with a familiar industry challenge: the high cost of production and licensing, which often makes it difficult to livestream cultural and sports events at scale.
“Many cultural and sports competitions are never livestreamed because traditional broadcasting is too costly and complex”, said Chengcheng Li, Founder of Mitico. “By distributing a centralised production feed through creators and community hosts, regional events can reach global audiences while maintaining a unified production workflow”.
World of Dance (WOD) offered a natural test environment. It started as a global dance competition platform before entering a television partnership with NBC, which later produced four seasons of the World of Dance reality series. While the television programme concluded in 2021, the competition business has continued to expand through an international network of partners. Today, World of Dance competitions are represented in more than 72 countries, producing nearly 100 events each year, with a digital audience of more than 34 million followers across platforms
Despite that scale, many competitions are not livestreamed due to the high production costs and technical demands associated with traditional broadcasting. The Hong Kong event was selected to assess whether a community-led distribution model could offer a more scalable alternative for live coverage.
While no changes to World of Dance’s broader distribution strategy have been announced, the Hong Kong pilot offers an early indication of how global competitions may rethink livestreaming in an increasingly creator-driven media environment.
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A look at how motivation, not metrics, is becoming the real frontier in fitness tech
Updated
February 7, 2026 2:18 PM
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.