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As artificial intelligence makes it easier to write code, a different problem is starting to surface. Building software is no longer limited by technical skill alone. Increasingly, the challenge lies in deciding what to build, how to structure it, and how to turn an idea into something that actually works.

That shift sits at the centre of BrainGrid, a startup that has raised $1 million in pre-seed funding led by Menlo Ventures, with participation from Next Tier Ventures and Brainstorm Ventures. The company is building what it describes as an AI-powered planning layer for people who want to create software but may not have a technical background.

The timing reflects a broader change in how products are being built. Tools like Claude Code and Cursor have made it possible to generate working code through simple prompts. For many first-time founders, this has lowered the barrier to entry. But writing code is only one part of the process. Turning that code into a reliable product requires structure, sequencing and clarity—areas where many projects begin to fall apart.

In traditional teams, this responsibility sits with product managers who define what needs to be built and in what order. Without that layer, even well-written code can lead to products that feel disjointed or incomplete. Features may not work together, integrations can break and the final product often does not match the original idea.

BrainGrid is designed to address that gap. Instead of focusing on generating code, it helps users map out the structure of a product before development begins. The aim is to give builders a clearer starting point so that the tools they use—whether human or AI—can produce more consistent results.

The company says more than 500 builders have already used it to create software products across areas like fitness, healthcare and productivity. These range from first-time founders experimenting with new ideas to experienced developers working independently. In many cases, the products are already live and generating revenue, suggesting that the demand is not just for experimentation but for building something that can scale.

For investors, the appeal lies in the evolving role of software development. As AI takes on more of the technical work, the value shifts toward defining the problem and structuring the solution. In that sense, planning becomes less of a background task and more of a core capability.

The US$1 million raise is relatively modest, but it points to a larger trend. As more people gain access to AI tools, the number of potential builders expands. What remains limited is the ability to organise ideas into products that work in the real world. If that shift continues, the next wave of software may not be defined by who can code, but by who can plan.

As global tech ecosystems become more interconnected, the ability to move innovation across borders is becoming just as important as building it. A new partnership between MTR Lab, the investment arm of MTR Corporation and ZGC Science City Ltd, a government-backed technology ecosystem based in Beijing’s Haidian district, reflects this shift.

At its core, the collaboration is designed to connect high-potential Chinese startups with global capital, real-world deployment opportunities and international markets. It focuses on sectors like AI, robotics, smart mobility and sustainable urban development—areas where China already has strong technical depth but where scaling beyond domestic markets can be more complex.

This is where the partnership begins to matter. ZGC Science City sits at the center of one of China’s most concentrated innovation clusters, with thousands of AI companies and a growing base of specialised and high-growth firms. MTR Lab, on the other hand, brings access to international markets, industry networks and practical deployment environments tied to infrastructure, transport and urban systems. Together, they are attempting to bridge a familiar gap: turning local innovation into globally relevant products.

In practice, the model is straightforward. ZGC Science City will introduce MTR Lab to startups working in priority sectors, creating a pipeline for potential investment and collaboration. From there, MTR Lab can support these companies through funding, pilot projects and access to overseas markets. The idea is not just to invest, but to help startups test and apply their technologies in real-world settings, particularly in complex urban environments.

The timing is notable. China’s AI and deep tech ecosystem has expanded rapidly, with thousands of companies contributing to advancements in automation, smart infrastructure and sustainability. At the same time, global demand for these technologies is rising, especially as cities look for more efficient and scalable solutions. Yet, moving from innovation to adoption often requires cross-border coordination—something individual startups may struggle to navigate alone.

This partnership also builds on a broader pattern. Corporate venture arms like MTR Lab are increasingly positioning themselves not just as investors, but as connectors between markets. By combining capital with access to infrastructure and deployment scenarios, they offer startups a way to move faster from development to real-world use. For ZGC Science City, the collaboration adds an international layer to its ecosystem, helping local companies extend beyond domestic growth.

What emerges is a model that goes beyond a typical investment announcement. It reflects a growing recognition that innovation today is rarely confined to one geography. Technologies may be developed in one ecosystem, refined in another and scaled globally through partnerships like this.

As cross-border collaboration becomes more central to how startups grow, partnerships like the one between MTR Lab and ZGC Science City point to a more connected innovation landscape—one where access, not just invention, defines success.

As global tech ecosystems become more interconnected, the ability to move innovation across borders is becoming just as important as building it. A new partnership between MTR Lab, the investment arm of MTR Corporation and ZGC Science City Ltd, a government-backed technology ecosystem based in Beijing’s Haidian district, reflects this shift.

At its core, the collaboration is designed to connect high-potential Chinese startups with global capital, real-world deployment opportunities and international markets. It focuses on sectors like AI, robotics, smart mobility and sustainable urban development—areas where China already has strong technical depth but where scaling beyond domestic markets can be more complex.

This is where the partnership begins to matter. ZGC Science City sits at the center of one of China’s most concentrated innovation clusters, with thousands of AI companies and a growing base of specialised and high-growth firms. MTR Lab, on the other hand, brings access to international markets, industry networks and practical deployment environments tied to infrastructure, transport and urban systems. Together, they are attempting to bridge a familiar gap: turning local innovation into globally relevant products.

In practice, the model is straightforward. ZGC Science City will introduce MTR Lab to startups working in priority sectors, creating a pipeline for potential investment and collaboration. From there, MTR Lab can support these companies through funding, pilot projects and access to overseas markets. The idea is not just to invest, but to help startups test and apply their technologies in real-world settings, particularly in complex urban environments.

The timing is notable. China’s AI and deep tech ecosystem has expanded rapidly, with thousands of companies contributing to advancements in automation, smart infrastructure and sustainability. At the same time, global demand for these technologies is rising, especially as cities look for more efficient and scalable solutions. Yet, moving from innovation to adoption often requires cross-border coordination—something individual startups may struggle to navigate alone.

This partnership also builds on a broader pattern. Corporate venture arms like MTR Lab are increasingly positioning themselves not just as investors, but as connectors between markets. By combining capital with access to infrastructure and deployment scenarios, they offer startups a way to move faster from development to real-world use. For ZGC Science City, the collaboration adds an international layer to its ecosystem, helping local companies extend beyond domestic growth.

What emerges is a model that goes beyond a typical investment announcement. It reflects a growing recognition that innovation today is rarely confined to one geography. Technologies may be developed in one ecosystem, refined in another and scaled globally through partnerships like this.

As cross-border collaboration becomes more central to how startups grow, partnerships like the one between MTR Lab and ZGC Science City point to a more connected innovation landscape—one where access, not just invention, defines success.

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At NVIDIA GTC 2026 in Palo Alto, a group of 16 Taiwanese startups used the global AI stage to do more than showcase products—they tested how far their technologies could travel beyond domestic markets. The delegation, led by Startup Island TAIWAN Silicon Valley Hub with support from Taiwan’s National Development Council, reflected a broader shift in the country’s role within the AI ecosystem.

The startups represented a mix of emerging areas including digital twins, robotics, AI agents and healthcare, aligning closely with enterprise AI adoption trends. Some gained formal visibility within NVIDIA’s ecosystem, with companies such as MetAI and Spingence featured in the Inception Program, while six others presented their work in the conference’s poster gallery. These formats allowed them to engage directly with developers, enterprise users and potential partners rather than simply exhibiting technology.

A defining feature of Taiwan’s presence this year was how closely startups operated alongside established hardware companies such as ASUS, AAEON and Compal. This setup reflected a vertically integrated model where infrastructure and applications are developed together, offering a clearer path from product development to deployment. It also underscored Taiwan’s gradual shift from being primarily a hardware supplier to participating more actively across the full AI stack.

Activity around the conference extended well beyond the exhibition floor. A Taiwan Demo Day held during the week drew more than 1,000 registrations and nearly 600 in-person attendees, bringing startups into contact with close to 200 international investors. The event focused on structured introductions and deal flow, positioning startups in front of venture firms and corporate innovation teams looking for AI applications.

Alongside these formal sessions, Taiwan Startup Night provided a more informal but equally strategic setting. With over 100 curated participants, including founders, investors and corporate representatives, the gathering created space for early-stage conversations that could evolve into partnerships or market entry opportunities. These interactions, while less visible than on-stage presentations, are often where initial collaboration takes shape.

Taken together, the events around GTC point to a more coordinated approach to international expansion. Through platforms like Startup Island TAIWAN, the emphasis is not just on visibility but on building continuity—connecting startups with investors, partners and customers across multiple touchpoints in a single week. As AI development increasingly spans chips, systems and applications, Taiwan’s presence at GTC suggests a more integrated role, where the focus is as much on enabling global deployment as it is on developing the technology itself.

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Airports are some of the most complex systems in the world. Every day, they manage thousands of flights, passengers, crew schedules, gates and ground operations—all moving at the same time. But much of this still runs on older software that doesn’t connect well, making simple decisions harder than they need to be.

This is the gap companies like AirportLabs are trying to address. Instead of relying on multiple disconnected systems, their approach brings airport operations into one cloud-based platform. The goal is straightforward: take scattered data and turn it into something teams can actually use in real time.

In practice, this means combining core systems like flight databases, resource management and display systems into a single interface. When everything is connected, airport staff can respond faster—whether it’s adjusting gate assignments, managing delays, or coordinating ground crews. Rather than reacting late, decisions can be made as situations unfold.

Another shift is how this technology is built. Traditional airport systems often require heavy on-site infrastructure and long deployment timelines. In contrast, cloud-based platforms remove much of that complexity. Updates are faster, systems are easier to scale and teams spend less time maintaining servers and more time improving operations.

What stands out is the speed of adoption. Instead of multi-year rollouts, newer systems can be implemented in weeks, allowing airports to see improvements much sooner.

At a broader level, this reflects a familiar pattern seen across industries. As operations become more data-heavy, the advantage shifts to those who can simplify complexity. In aviation, that doesn’t just mean better technology—it means making the entire system easier to run.

Coffee has grown beyond being just a drink—it’s part of culture, connection and even a daily productivity hack. Think about it: friends catch up over cappuccinos, professionals start the day with a quick espresso and students practically live on iced lattes during exams. It’s woven into routines, with two-thirds of American adults consuming coffee on a daily basis and averaging around three cups per day. That is much higher than other beverages like tea, juice and bottled water. It is therefore no surprise that the global coffee shop industry is projected to reach about US$123.43 billion by 2030. For entrepreneurs, that makes coffee shops more than cozy corners with good aesthetics. They’re a real business opportunity. But before you open a coffee shop, here are five things you should know.

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1. Coffee shop location matters more than you think

Like any small business, the success of your coffee shop often hinges on where it is. Coffee may have broad appeal, but daytime foot traffic and visibility can still make the difference between a busy café and one that struggles to stay afloat. Opening near universities, office parks, co-working hubs or residential neighbourhoods with young professionals can instantly give you a strong stream of potential customers.

That said, choosing a coffee shop location is not just about picking a busy area. You also need to know your target market. For example, opening a third-wave specialty coffee shop in a low-income neighbourhood may not work if your prices are beyond what local residents want to pay. The same café might perform much better in a more affluent or fast-changing district.

Competition matters a lot in the equation too. Walk around the area and see what other coffee shops are doing. The goal is not always to avoid competition but to find a gap in the market. If nearby cafés focus on quick grab-and-go drinks, there may be room for a slower, more community-driven coffee shop built around hand-poured brews and a relaxed atmosphere. Simply put, your shop’s exact street address could make or break your business.

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2. In the coffee business, customer experience matters

It’s important to understand this early on: running a coffee shop is not just about serving coffee. Customers today have endless options, from making coffee at home to buying from major chains like Starbucks. What brings them through your doors is often the overall experience.

According to a report by Salesforce, 91% of customers say they’re more likely to make another purchase after a great service experience. That means your café needs to give people a reason to stay, come back and recommend it to others. Maybe it is the interior design, the playlist that feels just right, the reliable Wi-Fi, the convenient charging points or simply the way the space feels. Remember, good coffee gets people in once, but a strong customer experience gives them a reason to return.

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3. Know your coffee shop costs before you make your first brew

Opening a modest-sized sit-down café in the U.S. can cost anywhere between US$100,000 and US$350,000. The final number depends on your location, your coffee shop concept, your equipment and how much you spend on the fit-out and interior design. Beyond those startup costs, your monthly expenses—like rent, utilities, staff salaries and coffee bean purchases—will play a huge role in whether your business survives the first year.

Profit margins in coffee retail are thinner than new owners expect. On average, small to medium-sized coffee shops make a 3-10% profit margin, which means efficiency is key. Selling higher-margin items like snacks, light bites and pastries can help lift revenue. A US$2 slice of banana bread, for example, may cost cents to make but can still raise the average spend per customer.

You also need to factor in seasonality when planning your coffee shop revenue. For instance, in warmer months, there is usually higher demand for iced and cold beverages. Many cafés respond by introducing cold brew, iced teas, smoothies or limited seasonal drinks to their menus. That helps keep sales steady and protects the average ticket size throughout the year. At the end of the day, running a café is just as much about managing the numbers as it is about serving great coffee.

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4. Baristas are your frontline brand ambassadors  

A barista isn’t just someone pulling espresso shots; they’re often the face of your coffee shop. A warm smile, remembering a regular’s order or sharing a fun fact about the beans can create the kind of connection that keeps customers coming back.

As specialty coffee culture boomed in the early 2010s, baristas became more than brewers—they are now guides and storytellers. By talking about coffee origin, processing methods, bean varieties and roast profiles, they help customers understand what they are buying and why it matters. That mix of knowledge and personality can have a real impact on customer loyalty.

That’s why hiring and retaining great baristas is one of the smartest investments a café owner can make. Beyond competitive pay, creating a workplace where people feel valued also matters. Training, room for creativity and a sense of pride in the craft can go a long way in helping staff stay engaged.

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5. Coffee shop marketing must go beyond “Opening Soon” posters  

Opening a coffee shop is exciting, but opening the doors and hoping people walk in is not enough. Good coffee shop marketing today is less about spending big and more about telling a story people want to follow. Well before you launch, start building hype and share behind-the-scenes snippets on Instagram, whether that is taste-tests, design decisions or even the messy parts of setting up the space. That kind of content feels real and helps build anticipation.

Once your café is open, think beyond basic promotion. Loyalty programs, collaborations with local businesses or even hosting events like poetry nights, art exhibits or coffee cupping sessions can all help bring people in. Social media is useful here too; it is not only a place to post latte art but also where you show what your brand stands for. Do you focus on sustainability? Do you source coffee ethically? Do you support local artists? Those details humanize your brand and make your café more than just a pitstop for caffeine.

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Brewing it all together

Overall, opening a coffee shop blends passion, community and entrepreneurship. It also requires clear thinking and strong business decisions. From choosing the right location and creating a memorable customer experience to managing costs and building a great team, success takes more than just brewing good coffee. If you treat your coffee shop as both a craft and a business, you give it a much better chance of becoming a local favourite.

Endometriosis affects roughly one in ten women worldwide, yet diagnosing the condition often takes years. In many cases, patients experience symptoms for nearly a decade before receiving a confirmed diagnosis. One reason is that detecting endometriosis through ultrasound requires specialized training and clinicians do not always encounter enough real cases to build that expertise.

To address this gap, medical simulation company Surgical Science has introduced a new ultrasound training module designed specifically for identifying endometriosis. The system allows clinicians to practice scanning techniques in a virtual environment, helping them recognize signs of the disease without relying solely on real-patient cases.

A key feature of the simulator is training on the “sliding sign,” an ultrasound indicator used to detect deep endometriosis. Because the condition can appear differently from patient to patient, mastering this assessment in real clinical settings can be difficult. The simulator allows clinicians to repeat the process across multiple scenarios, improving their ability to identify the condition during routine examinations.

The module also incorporates the International Deep Endometriosis Analysis (IDEA) protocol, which provides a structured method for performing a complete pelvic ultrasound assessment. Additional training cases, region-based scenarios and certification options are included to support standardized learning.

Early training results suggest strong improvements in clinician confidence, including higher skill levels in transvaginal ultrasound and better recognition of deep endometriosis. By expanding access to structured ultrasound training, simulation tools like this could help reduce diagnostic delays and improve care for millions of women living with the condition.

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People often assume robots make people uneasy everywhere. But a new global study suggests something more nuanced. Robot anxiety tends to be highest in places where people rarely see robots in real life. Where robots are more visible, attitudes are often far more positive. That insight comes from a global study by Hexagon AB, which surveyed 18,000 participants across nine major markets. The research explored how adults and children think about robots and how those views change depending on everyday exposure.

In the United Kingdom, anxiety about robots is the highest among the countries studied. Around 52% of adults say they feel worried that something might go wrong when they think about interacting with or working alongside robots. South Korea sits at the other end of the spectrum, with only 29% reporting similar concerns. One factor appears to explain much of the gap: familiarity.

British adults are among the least likely to have encountered robots in real life. Only about 30% say they have seen or used one. In contrast, countries where robots are more visible tend to report greater comfort. China offers the clearest example. Around 75% of adults there say they have seen or interacted with robots. At the same time, 81% say they feel excited about the technology’s future potential.

The study suggests that attitudes toward robots are not fixed. Instead, they shift depending on where people encounter them and what tasks they perform. When robots are seen solving clear, practical problems, confidence tends to rise.

Across the surveyed countries, adults report the highest comfort levels with robots working in factories and warehouses. Around 63% say they are comfortable with robots in those environments. These are settings where tasks are clearly defined and safety standards are well understood. Acceptance drops in more personal spaces. Only 46% say they feel comfortable with robots in the home, while comfort falls further to 39% when robots are imagined in classrooms.

In other words, context matters. People appear more willing to accept robots when they take on physically demanding or dangerous work. Half of the respondents say improved safety is one of the main advantages of robotics in those environments. A similar share point to productivity gains as another benefit. Another finding challenges a common assumption about public fears. Job loss is often described as the biggest concern surrounding robotics. But the study suggests security risk worries people more.

Around 51% of adults say their biggest concern about robots at work is the possibility that the machines could be hacked or misused. That fear outweighs worries about physical malfunction or injury, which stand at 41%. Concerns about being replaced at work appear at the same level.

For many respondents, the issue is not simply whether robots can perform tasks. It is whether the systems controlling them are secure. According to researchers involved in the study, these concerns reflect how people evaluate emerging technologies. Instead of having a single opinion about robotics, people tend to judge each situation individually.

A robot helping assemble products in a factory may feel acceptable. The same technology operating in more sensitive environments can raise different questions. Dr. Jim Everett, an associate professor in moral psychology, says trust in artificial intelligence and robotics is often misunderstood. People are not simply asking whether they trust the technology, he notes. They are thinking about specific tools performing specific roles.

A robot assisting in a classroom or helping in healthcare carries different expectations than an AI system used in defense or surveillance. Even though these technologies are often grouped together in public debates, people evaluate them differently depending on their purpose.

Finally, the study also highlights another important factor shaping public attitudes: experience. When people actually encounter robots, fear often declines. Michael Szollosy, a robotics researcher involved in the project, says reactions tend to change quickly when individuals meet a robot for the first time.

The idea of an autonomous machine can feel intimidating in theory. But when people see a small service robot or an industrial machine performing a straightforward task, the reaction is often much calmer. Exposure can shift perceptions from abstract fears to practical understanding.

That shift matters because robotics is moving steadily into everyday environments. From manufacturing and logistics to healthcare and public services, machines capable of autonomous or semi-autonomous work are becoming more common.

As that happens, the study suggests public confidence may depend less on technical breakthroughs and more on visibility and transparency. Burkhard Boeckem, chief technology officer at Hexagon AB, argues that trust grows when people understand what robots are designed to do and where their limits lie.

Anxiety tends to increase when systems feel invisible or poorly understood. Clear boundaries and clear explanations can have the opposite effect. When people see robots working safely alongside humans, performing well-defined tasks and operating within clear rules, the technology becomes easier to accept.

In that sense, the future of robotics may depend as much on public familiarity as on engineering. The machines themselves are advancing quickly. But the relationship between humans and robots is still being negotiated. For now, the study offers a simple insight: the more people encounter robots in everyday life, the less mysterious they become. And once the mystery fades, the conversation often changes from fear to curiosity.

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As Hollywood prepares for this weekend’s Oscars, a different kind of performer is stepping into the spotlight — one that doesn’t physically exist.

Tilly Norwood, described as the world’s first AI actor, has released her debut musical comedy video, Take the Lead. The project arrives at a moment when artificial intelligence has become one of the most contentious topics in the film industry.

The message of the song is simple. AI should not be seen as a threat to actors. Instead, it can become another creative tool. The release also offers a first look at what Norwood’s creators call the “Tillyverse”. It is envisioned as a cloud-based entertainment world where AI characters can live, interact and perform.

Behind the character is actor and producer Eline van der Velden. She is the CEO of production company Particle6 and AI talent studio Xicoia. Van der Velden created Tilly as a way to experiment with how artificial intelligence could be used in storytelling.

The timing is not accidental. The entertainment industry has spent the past few years debating the role AI should play in filmmaking and acting. Questions about digital replicas, automated performances and creative ownership continue to divide artists and studios.

Norwood’s musical video enters that debate with a different tone. Instead of warning about AI replacing actors, the project suggests that the technology could expand what performers are able to do.

The video itself also serves as a technical experiment. The song Take the Lead was generated using the AI music platform Suno. The video was then produced using a combination of widely available AI tools and Particle6’s own creative process.

One of the newer techniques used in the project is performance capture. Van der Velden physically acted out Tilly’s movements and expressions so the digital character could mirror a human performance. But the production was far from automated. According to Particle6, a team of 18 people worked on the video. The group included a director, editor, production designer, costume designer, comedy writer and creative technologist. In other words, the project still relied heavily on human creativity.

“Tilly has always been a vehicle to test the creative capabilities and boundaries of AI,” van der Velden said. “It’s not about taking anyone’s job”. She added that even with powerful tools, good AI content still takes time, taste and creative direction.

The project also reflects how quickly production technology is evolving. Tools that once required large studios are now accessible to smaller creative teams experimenting with AI-driven storytelling.

For Particle6, the character of Tilly Norwood acts as a testing ground. Each project explores how AI performers might be developed, directed and integrated into entertainment. Whether audiences embrace digital actors remains an open question. Many in the industry are still wary of how AI could reshape creative work.

But projects like Take the Lead show another possibility. Instead of replacing performers, artificial intelligence could become part of the creative process itself. In that sense, Tilly Norwood may represent something more than a virtual performer. She is also an experiment in how humans and machines might collaborate in the future of entertainment.

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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