Bixberry launches a network that keeps AI current, and rewards people who help

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AI has become part of daily life. It writes, codes, answers questions, and handles tasks that used to take hours. But there is one thing even the most advanced model cannot do on its own: it cannot see today’s world. Every model stops learning the day it is built, so to answer anything about the present, it has to reach the live internet and check.

This is the gap Bixberry was built to close. The company describes itself as a premium real-time access network for AI, and the job it does is a specific one: helping AI systems retrieve fresh, real-world information from the live web, drawn from the idle internet of everyday devices.

Why AI needs real people

According to Bixberry, when an AI model checks the web, it does not always see the same thing a real person would. Websites routinely serve different content based on where a visitor appears to be connecting from, adjusting prices, currency, language, and local availability to match the visitor’s location. This is standard practice: Cloudflare, one of the world’s largest web infrastructure providers, documents how sites tailor content by a visitor’s country, such as showing prices in the local currency. So a request coming from a real connection in a particular place tends to see that location’s version of a page, while a model reaching the web from a distant data center may not.

That is why real people matter to AI. A model sitting in a data center sees the world from far away and from the past. A network of real connections, in real places, can give it a current, local point of view. Ask for the newest restaurant in a city, or what something costs in a particular country, and the answer depends less on how clever the model is and more on whether it could see that part of the web the way a local does.

The reward model, reimagined

Bixberry turns that need into a role for everyday internet users. By sharing a small part of their idle internet, people help AI stay current, and they earn rewards for it.

This is a reward app built on genuine demand rather than busywork. Users install the app in around 30 seconds, let it run quietly in the background, and earn rewards over time. It uses only the idle internet on a device, without interfering with everyday use.

Unlike apps that ask people to log in daily or complete repeated actions to earn, Bixberry runs on its own in the background. The company’s view is that an app should do its job rather than constantly compete for your time.

Bixberry estimates that US users can expect to earn roughly $10 to $30 per month, depending on network availability and location. The company describes this as its own estimate, based on typical device usage and how often a connection is drawn on, and notes the figure is modest by design. The rewards are hands-off: value earned while a device sits idle, with no logging in and no tasks to complete.

Why this cannot simply be built

There is a reason AI companies cannot easily solve this by building more of their own infrastructure. The industry is already straining against physical limits. According to the International Energy Agency, a typical AI-focused data centre consumes as much electricity as 100,000 households, while the largest ones under construction today will use twenty times as much. Data centre electricity use is projected to more than double to around 945 terawatt hours by 2030, slightly more than Japan’s total electricity consumption today, with AI the most important driver.

Even as companies invest billions of dollars into new data centers, building fresh, globally distributed access the conventional way runs into the same wall of land, power, and time. What Bixberry offers instead is capacity that already exists: billions of everyday devices, already online, already in the exact places AI needs to reach. Nothing new has to be constructed. The connections are simply there, waiting to be used with permission.

Sharing a connection is the kind of thing that has been done badly before: buried in the terms of a free app, running invisibly, with no clear way to stop it. Bixberry says its approach is built at the opposite end of that spectrum, and its Chief Product Officer describes the difference plainly.

“The thing people don’t realize about AI is that it stops learning the day it ships. The world obviously doesn’t stop. So someone has to keep it connected to what’s actually happening, and honestly, that part doesn’t come from a data centre, it comes from regular people who agreed to share their connection. That’s the product. You know what you signed up for, you can watch it work, and if you don’t like it, you turn it off. That’s it,” said Bixberry CPO Egle Maldute.

The company says that principle runs through the whole design. According to Bixberry, participation is explicit and reversible: you install the app to share your connection, you can see it working, and one switch stops it. The company says it does not access the private contents of a device and draws only on idle internet to reach publicly available information. It also says every partner on the network is a verified business, vetted before any traffic flows, and that the only traffic carried is AI reading the public web the way a person would. Bixberry says the platform was built around consent and transparency from the outset, and designed to meet GDPR and CCPA requirements.

Built on fair participation

For years, people have powered the internet and received little in return. Bixberry’s argument is that the value should flow both ways: real demand on one side, real reward on the other, with transparency underpinning both. Rather than paying out points for busywork, the network rewards people for something genuinely useful, helping AI stay accurate and current.

The demand behind it is not a passing trend. Because the world changes every day, AI’s need to re-check it never stops, which makes this a lasting role rather than a one-time opportunity.