A wearable ring, conversational AI and US$23M in funding. Sandbar wants to rethink how we interact with technology
Updated
March 12, 2026 5:59 PM
Sandbar's Stream ring. PHOTO: SANDBAR
Sandbar, a New York–based interface startup, has raised US$23 million in Series A funding to develop a wearable device that lets people interact with artificial intelligence via voice rather than screens.
Adjacent and Kindred Ventures led the round; both venture firms focused on early-stage technology startups. The investment brings Sandbar’s total funding to us$36 million. Earlier backing included a US$10 million seed round led by True Ventures, a venture capital firm, as well as a US$3 million pre-seed round supported by Upfront Ventures, a venture firm and Betaworks, a startup studio and investment firm.
Sandbar was founded by Mina Fahmi and Kirak Hong, who previously worked together at CTRL-labs, a neural interface startup acquired by Meta in 2019. Their earlier work explored how computers could respond more directly to human intent — an idea that continues to shape Sandbar’s approach to AI interfaces.
The new funding will help the company expand its team across machine learning, interaction design and software engineering as it prepares to launch its first product. That product, called Stream, combines a wearable ring with a conversational AI interface. The system allows users to speak to an AI assistant without unlocking a phone or opening an app.
The concept is simple. Instead of typing into a screen, users press a button on the ring and talk. The system can capture notes, organize ideas, retrieve information from the web or trigger actions through connected applications.
The ring includes a microphone, a touchpad and subtle haptic feedback. These elements allow the device to respond through gentle vibrations rather than visual alerts. According to the company, the ring only listens when the user presses the button — a design meant to address common concerns around always-on microphones.
That design reflects a larger shift Sandbar believes is underway. As AI assistants become more capable, many startups are experimenting with new ways to interact with them. The focus is moving away from screens and keyboards toward interfaces that feel more natural and immediate.
Stream uses multiple AI models working together to process requests, search the web and structure information in real time. The company says users remain in control of their data and can choose whether to share information with other apps.
Sandbar is also developing a feature called Inner Voice, which responds using a voice customized to the user. The feature will debut during a closed beta planned for this spring, giving the company time to refine how the software behaves in everyday use.
The startup currently employs a team of 15 people. Many have worked on well-known consumer devices including the iPhone, Fitbit, Kindle and Vision Pro. Recent hires include Sam Bowen, formerly of Amazon and Fitbit, who joined as vice president of hardware and Brooke Travis, previously at Equinox, Dior and Gap, who now leads marketing.
Sandbar plans to begin shipping Stream in summer 2026 after completing early testing. As artificial intelligence tools become more integrated into daily life, the company is betting that the next shift in computing will not come from another app — but from new ways for people to interact with AI itself.
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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.