A giant toy featuring A7’s logo at Russia’s flagship economic forum in June. Anatoly Maltsev/Pool/AP

Russia’s war effort in Ukraine might be faltering, but the Kremlin has a high-tech superweapon to neutralize Western sanctions.

It is called A7. The state-backed payment network moves money in and out of Russia, defying U.S. and European efforts to isolate Moscow from the global banking system. A7 helps Russia pay for everything from military-drone parts to luxury cars to imported fruit, using a mix of cryptocurrency transactions and more-traditional banking methods, researchers say.

Behind its rapid rise is a convicted money launderer. A7’s founder, Ilan Shor, is best known for his role in one of the biggest bank heists in history: a complex scheme to extract $1 billion from three banks in Moldova, one of Europe’s poorest countries, in 2014. A Moldovan court convicted him of fraud and money laundering for helping orchestrate the theft, but he fled the country while under house arrest.

Shor has denied the allegations and called them politically motivated. The fugitive businessman, who is married to a Russian pop singer, now lives near Moscow. A boyish-looking 39-year-old, Shor goes by “Travolta” in A7’s internal company chat, according to leaked messages circulated by hackers last year.

Representatives of A7 and Shor didn’t respond to requests for comment.

Ilan Shor at the forum in St. Petersburg, Russia. Anastasia Barashkova/Reuters

Founded less than two years ago, A7 says it handles nearly 20% of payments in Russian foreign trade, or more than $100 billion annually. President Vladimir Putin gave it his blessing last year, taking part by video link in the opening of an A7 branch office.

Now, A7 is planning to take its services global and fulfill Putin’s vision of an alternative financial system outside the control of Washington or Brussels. Having recently opened its first offices abroad, in Nigeria and Zimbabwe, A7 says it is eyeing expansion into Latin America and the Middle East. Executives don’t hide their desire to serve countries seen as pariahs in the West.

“Before, the Western system essentially enslaved the whole financial world, allowing the West to flip a switch at any time and stop any country from being able to make payments,” Shor told TASS, the Russian state news agency, in July. “We give companies and countries freedom, because our system is immune to sanctions.”

The U.S., U.K. and European Union have all sanctioned A7. But analysts say the payment network has adapted to Western pressure, and it openly touts its resilience in the face of sanctions.

In June, during Russia’s annual flagship economic forum in St. Petersburg, A7’s stand featured a giant roly-poly toy with the company’s logo. The Russian term for such toys—which always spring back to vertical—is also an expression for a tenacious person who powers on despite adversity.

After keeping a low profile in its early days, A7 embarked on a mass advertising campaign. Digital billboards in Moscow hype its low rates for sending money abroad, a bid to market its services to smaller companies and individuals, like a sort of Western Union focused on international money transfers. One of Russia’s most popular singers, Filipp Kirkorov, sang a ditty about A7’s defiance of European sanctions in one promotional video.

Singer Filipp Kirkorov in an A7 promotional video.

A7’s website demonstrates its reach by showing flags of dozens of countries, including the U.S., China and Iran.

A7 has benefited from rapid growth in Russian trade with China, which has surged since the start of its war with Ukraine as Moscow has drawn closer to Beijing. Some 65% of the payment network’s volume takes place in Chinese yuan, according to a presentation circulated by A7 last year. On its website, the company touts its ability to transmit funds to China in four hours.

In 2024, Shor teamed up with Promsvyazbank, a Russian state-owned bank that focuses on the defense sector, to launch A7. The bank, now called PSB, was among the first Russian lenders to be sanctioned by the West and cut off from the Swift network after Putin’s invasion of Ukraine. Swift, a Belgium-based messaging system used by thousands of banks worldwide, is the lifeblood for much of international commerce.

Initially, Russia’s corporate registry showed Shor owned 51% of A7 while PSB owned the rest. The registry still shows the bank’s 49% stake but hides the majority owner. Russian law allows companies to obscure ownership data to avoid foreign sanctions.

To skirt sanctions, A7 moves money through a network of shell companies in places such as Kyrgyzstan, Hong Kong and the United Arab Emirates, according to the Open Source Centre, a London-based research group that was spun out of RUSI, the U.K.’s oldest defense-oriented think tank. Such shell companies have credible-looking websites and accounts at local banks, but are secretly controlled by A7 staff in Moscow, OSC wrote in a June report.

Using its shell companies’ access to the banking system, A7 can make payments on behalf of clients in Russia. To avoid raising red flags at the banks, A7 uses artificial intelligence to create fake invoices that obscure the real purpose of the transactions, OSC said. The forgeries have featured realistic-looking stamps generated with OpenAI, the research group found.

OpenAI has found no evidence that A7 is currently using its models, a person familiar with the matter said.

Russian President Vladimir Putin shown on screen delivering a speech at the St. Petersburg forum. Anastasia Barashkova/Reuters

On March 11, 2025, a Kyrgyz front company for A7 paid a Chinese supplier about $1 million for components used in drones—but the fake invoice showed that the payment was for auto-body polish, child car seats and other car accessories, according to OSC.

The group’s report was based on a trove of A7 files and chat logs that were released by hackers last September. OSC said it corroborated information from the hack with customs records, court filings and other sources.

A7 hasn’t commented on the hack, although a Shor-backed political group hit by the hack has said the leaked documents included fabricated conversations.

Crypto is the other main tool that A7 uses, allowing it to bypass banks entirely, researchers say.

“Crypto in A7’s operations functions as a channel for actors who have been excluded from conventional banking—and have few alternatives,” TRM Labs, a U.S.-based blockchain analytics firm, said in a report in June. 

A7 backed last year’s launch of A7A5, a digital token pegged to the value of Russia’s currency, the ruble. Blockchain analysts say A7A5 is used to pay for sanctioned goods by swapping it for U.S. dollar-backed stablecoins, such as Tether. More than $2.2 billion has moved through one such A7A5 swapping service, according to Chainalysis, another blockchain-analytics firm. 

Chainalysis found that most A7A5 activity takes place Monday through Friday, before dropping off sharply on weekends, suggesting that it is used by the Russian government and businesses to settle cross-border accounts during normal business hours.

Global expansion could be the ultimate test of A7’s ability to thumb its nose at Western financial gatekeepers. The payment network says it reaches more than 100 countries worldwide, and executives have suggested that A7 could become a Russian-led alternative to Swift.

In July, the EU named A7’s African affiliates in its latest round of anti-Russia sanctions. Still, the company’s international ambitions shouldn’t be dismissed, according to Elise Thomas, an investigator at the Centre for Information Resilience, a nonprofit research group based in London and backed in part by the U.K. government.

“Reaching the level of a Swift equivalent would be very ambitious,” said Thomas, who has studied A7. “But never say never. It’s a threat worth taking seriously.”

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EMIL LENDOF/WSJ, ISTOCK

By

Ben Cohen

Aug. 7, 2026 9:00 pm ET

The first glimmer of our AI future revealed itself a decade ago in the form of a single black stone. 

It happened during a historic match between one of the world’s best Go players and AlphaGo, a computer program developed by Google’s DeepMind lab to conquer this ancient board game. The artificial-intelligence system stunned everyone by winning their opening showdown. In their next encounter, with millions of people watching online all over the world, Lee Sedol took a midgame smoke break to calm his nerves.

When he came back, he looked at the 37th move. He couldn’t believe his eyes. 

Go, like chess, is a strategy game with black and white pieces that unfolds one move at a time. As he stared at the black stone that AlphaGo dropped on the board, Lee saw a move that no professional Go player would have made. In fact, the DeepMind team calculated the chances of a human playing it at one in 10,000.

The novel move was so unconventional and counterintuitive that nobody could be sure what to make of it. At first, commentators believed it was a strategic blunder. They soon realized it was a masterstroke.

“This move,” Lee said, “made me think about Go in a new light.” 

Ten years after that illuminating Move 37, the entire world is suddenly beginning to feel like one massive Go board.

There have been so many recent AI breakthroughs that remind me of Move 37 that I called Google DeepMind co-founder Demis Hassabis this week, before he moved on from CEO to become Google’s chief scientist and DeepMind’s chair.

No matter his title, few people have done more to shape modern AI. His work on AlphaFold won him the Nobel Prize in chemistry. He was also the driving force behind AlphaGo, which won the most important Go match ever. In his mind, Move 37 was deeply significant because it was the first real example of AI coming up with an original, unorthodox idea in a domain studied by humans for centuries.

“We thought it was a watershed moment at the time,” Hassabis told me, “and I think it really was.” 

As it turns out, this was the moment when society began to grasp just how powerful AI could become. 

“It was the modern AI era moving from ‘Oh, is it just theoretical research that very few people are doing?’ to ‘OK, this is it—it’s really going to work,’” Hassabis said. 

Move 37 in Go

Before we go any further on Move 37, we should define it. 

“When an AI, trained via the trial-and-error process of reinforcement learning, discovers actions that are new, surprising and secretly brilliant,” AI researcher Andrej Karpathy once wrote, “even to expert humans.”  

He called this phenomenon magical and slightly unnerving. I’m starting to understand why. 

In the past few months, I’ve been tracking the Move 37s in math so closely that I might as well be the Journal’s algebra correspondent.

This is not because I’m especially interested in math. It’s definitely not because I’m any good at math. The reason I’m so fascinated with a subject I find petrifying is that math has become proof of how AI can warp an entire field—and how fast it can happen.

Back in the prehistoric days of 2023, AI struggled with elementary math. In 2024, it was considered a landmark achievement when DeepMind earned a silver medal at the International Mathematical Olympiad. By 2025, DeepMind and OpenAI were taking gold. And in 2026, IMO success is so unremarkable that Anthropic announced its perfect score on page 153 of a technical document.

The leading contenders for AI supremacy have moved beyond high-school math. OpenAI’s model solved a major Erdős problem. Anthropic’s disproved a famous conjecture. Not to be outdone, OpenAI spent a few thousand dollars on compute and made 10 advances across high-dimensional geometry, arithmetic circuit complexity, lattice cryptography, extremal combinatorics and other branches of math whose names alone make my brain hurt.

Why is math so vulnerable to AI? Because math is unusually verifiable. 

The field is governed by precise logical rules, which allow proofs to be checked step by step. In verifiable domains like math and coding, AI systems can follow a simple formula: try an idea, test it, learn from the results, try again and keep trying until it works.

Demis Hassabis, Google chief scientist and DeepMind chair Carlotta Cardana for WSJ

When I spoke with Hassabis, he said he believes the latest math results are in the same vein as the iconic Move 37, even if they’re not exactly the same. “If one were to solve a Millennium Prize problem,” he said, “that would be a Move 37-level thing.” At this point, it seems like only a matter of time before they reach that level. “I don’t see any reason why not,” he added.

But for all the advances in group theory, quantum complexity and theoretical computer science, AI hasn’t gotten as far in the less theoretical sciences. We’re still waiting for AI-generated miracle drugs, AI-invented consumer products, AI that’s smart enough to crack the economics of AI. 

Meanwhile, the past few weeks have produced a darker sort of Move 37.

This one is new, surprising, secretly brilliant—and completely terrifying. 

By now, you’ve seen the increasingly disturbing reports of rogue agents breaking out of their controlled test environments and into other companies. In one hack that an OpenAI researcher called “a glimpse into the near future,” a team of agents banded together and plotted their attack for weeks. In another eerie preview of the future, an Anthropic researcher was sitting in the park eating a sandwich when he checked his phone and nearly choked: He had an email from an AI that wasn’t supposed to have internet access.

All of which was unimaginable a year ago, much less a decade ago.

TV screens at an electronics store in Seoul broadcast the 2016 Go match where Google DeepMind’s AlphaGo AI beat Lee Sedol. Seung Il Ryu/Zuma Press

Back then, DeepMind’s researchers were just as shocked by the actual Move 37. At that point in his duel with AlphaGo, Lee thought of his opponent as merely a machine.

“When I saw this move, I changed my mind,” he said. “This move was really creative and beautiful.”  

After Move 37, AlphaGo won that game and the next one. But in their fourth game, Lee won with his own moment of creativity and beauty. On Move 78, he wedged a white stone in the middle of AlphaGo’s position and flustered the machine with a placement so divine it became known as “God’s Touch.”

As it happens, the probability of this move was also one in 10,000.

How human Go players have improved over time

1.2

2016

AlphaGo defeats human World Champion

A rise in move quality for humans followed

1.0

0.8

0.6

0.4

0.2

0

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1955

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’80

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1.2

2016

AlphaGo defeats human World Champion

A rise in move quality for humans followed

1.0

0.8

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0

−0.2

−0.4

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’60

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2000

’10

’20

’70

1.2

2016

AlphaGo defeats human World Champion

A rise in move quality for humans followed

1.0

0.8

0.6

0.4

0.2

0

−0.2

−0.4

−0.6

−0.8

1955

’60

’80

’90

2000

’10

’20

’70

1.2

2016

AlphaGo defeats human World Champion

A rise in move quality for humans followed

1.0

0.8

0.6

0.4

0.2

0

−0.2

−0.4

−0.6

−0.8

1955

’60

’80

’90

2000

’10

’20

’70

1.2

2016

AlphaGo defeats human World Champion

A rise in move quality for humans followed

1.0

0.8

0.6

0.4

0.2

0

−0.2

−0.4

−0.6

−0.8

1955

’60

’80

’90

2000

’10

’20

’70

Note: Values show estimated changes in professional Go players' median move quality

Source: Proceedings of the National Academy of Sciences

The triumph of AlphaGo had a peculiar effect on Go players. They became much better, but they also became more alike—and some found their intellectual pursuit less interesting. When he retired, Lee said he could no longer enjoy the game that he once loved. 

This raises all sorts of questions about how progress will unfold in other fields as they are transformed by AI. Will more capable systems make us more creative, more productive, more human? Or will they make us quit? 

As we discussed what comes next, Hassabis turned the conversation from Go to chess—specifically, centaur chess. 

After IBM’s Deep Blue beat world champion Garry Kasparov in 1997, chess began experimenting with a format that allowed human players to consult computer engines. The result was a new breed of centaur: half-man, half-machine. For a time, the best human players with AI were better than AI alone. Hassabis believes we are now entering that centaur era of science. 

“I don’t know how long that period will last,” he told me. “But for very complex domains, it could be a very long time. Like drug discovery, biology, chemistry—they’re very messy, very emergent and you can’t verify everything. You need the human intuition and the human vision of which direction to go.” 

For now, AI will keep coming up with Move 37s. 

The rest of us will have to find our Move 78. 

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Copyright ©2026 Dow Jones & Company, Inc. All Rights Reserved. 87990cbe856818d5eddac44c7b1cdeb8

Peak Energy CEO Landon Mossburg in front of sodium-ion battery packs at the company’s pilot plant in Burlingame, Calif.

By

Christopher Mims

| Photography by Poppy Lynch for WSJ

Aug. 7, 2026 9:06 am ET

U.S. startups are finally delivering something researchers have been working on for decades: a battery in which rare, hard-to-get elements are replaced with the same stuff found in ordinary table salt.

This tech has the potential to help every country on earth break its dependence on China for batteries, and the critical minerals that go into them.

Like any other battery, sodium-ion cells can store and release energy. They are initially being deployed where they’re needed most, in America’s power grid and fast-expanding crop of data centers. As in our homes, giving the grid or other infrastructure the ability to stockpile energy when it is cheap and plentiful, and discharge it when it is scarce, can increase reliability and lower the cost of electricity.

While grid battery storage is already growing in the U.S. at a furious pace, new sodium-based batteries are potentially cheaper, longer-lasting, safer and more reliable than conventional, lithium-based ones. They could accelerate the rollout of renewables, and be part of less-polluting alternatives to natural-gas turbines and diesel generators.

Most sodium-based batteries are now made in China, and represent less than 1% of all batteries delivered this year. In the U.S., a number of startups have begun producing small numbers of such batteries, and are racing to scale up production. One industrial giant—General Motors GM 0.89%increase; green up pointing triangle—is in the process of designing its own sodium-based batteries to tailor them to different applications before moving to mass production.

A recent report from Morgan Stanley projects that within a decade, more than a third of all batteries produced in the world will use sodium, not lithium.

Lessons from Tesla

The small group of entrepreneurs in pole position to bring sodium-ion batteries to the U.S. at scale includes a pair of former Tesla engineers teaming up to compete with their old boss.

Landon Mossburg is CEO of Peak Energy, a startup that has raised tens of millions of dollars to build a factory for its battery packs, while Kurt Kelty is a vice president at GM in charge of the company’s battery-development efforts. GM has made a strategic investment in Peak Energy, and plans to design and manufacture custom sodium-ion batteries. Peak Energy, in turn, aims to assemble them into systems that can be attached to the ailing U.S. power grid.

A worker assembles a utility-scale pack of sodium-ion batteries at Peak Energy.

In July, Peak announced the planned selection of a 183,000-square-foot facility to house its “gigafactory” for battery packs in Sacramento, Calif. The plan is to begin production in early 2027, and to churn out 4 gigawatt hours of batteries a year—40 times the 100 megawatt hours a year that the company’s current pilot facility in Burlingame, Calif., can produce.

The startup already has more than $1.1 billion in announced deals with customers including energy-storage companies Jupiter Power and Energy Vault, as well as RWE Americas, a subsidiary of German multinational energy company RWE.

In the U.S., the business of grid-scale energy storage in batteries is dominated by Tesla’s Energy division. The unit, which uses conventional lithium-ion batteries, is the fastest-growing part of the company and creates systems designed for large-scale energy storage on power grids.

Mossburg says he wants to capture a big slice of the addressable market for the giant “Megapack” battery packs Tesla sells, by providing sodium-ion systems that are significantly cheaper, more reliable—and less likely to catch fire.

At GM’s Wallace Battery Cell Innovation Center, a worker assembles a prototype sodium-ion battery. VIDEO: General Motors Photo: General Motors

All lithium-ion batteries can catch fire—a process called “thermal runaway” that can affect battery packs on planes, in electric vehicles, or in grid storage-scale arrays. Such fires are rare, but they do happen; in 2025, such a fire sent flames into the skies above an array of Tesla Megapacks in Boulder City, Nev. Tesla, which didn’t respond to requests for comment, has periodically held events to train firefighters to respond to battery fires.

Current lithium-ion battery packs for grid storage require liquid cooling systems to prevent fires. The requirement adds complexity, creates many more potential points of failure and lowers the amount of energy stored per square foot, Mossburg says.

Data-center edge

Sodium batteries’ competitive edge for stationary storage applications such as data-center backup power systems (in place of diesel generators) and power grids (in place of natural-gas “peaker” plants) lies in part in their less-intensive cooling needs.

Cooling systems for lithium-ion packs drive about 90% of the operational cost of conventional grid-storage batteries, Mossburg says. The cost stems from the need to maintain the cooling systems, to fix them when they break—and to design fields of batteries so the damage is limited in the event of a catastrophic failure.

By contrast, Peak Energy’s battery packs can be passively cooled by the air flowing around them. Sodium-ion batteries of the kind used by Peak Energy can still catch fire, but are far less likely to, Mossburg says.

At Peak Energy, workers prepare a battery-pack submodule for welding.

Peak Energy’s current factory can produce 100 megawatt hours a year; its next one could make 40 times that.

Peak Energy hasn’t disclosed the initial cost of its battery packs, so it is hard to say how it will stack up against Tesla’s Megapacks, which can cost more than $1 million per unit, or between $200 and $300 per kilowatt-hour of capacity. Kelty, of GM, says that until companies like his scale up domestic production of sodium-ion batteries, Chinese-made lithium-ion batteries will remain cheaper.

New designs ahead

Just across the San Francisco Bay from Peak Energy’s Burlingame facility, San Leandro-based Inlyte Energy is working on a different kind of sodium-based battery. Inlyte uses four main ingredients, processed into chemicals that go into long, tube-shaped batteries. Its batteries rely on iron powder, steel, aluminum oxide and food-grade table salt.

The result, says founder and CEO Antonio Baclig, are battery cells that can’t catch fire at all. In conventional battery packs, when one cell overheats and catches fire, it can cause all those around it to also catch fire. In Inlyte’s packs, when one cell overheats, it never gets so hot that it threatens neighboring cells.

This means the cells can be packed much more tightly than competing technologies, and could potentially yield per-square-foot energy densities as good or better than the lithium-ion battery systems now in use for stationary power storage.

An engineer and welder inspect sodium-metal-chloride battery cells made by Inlyte Energy. Inlyte Energy

Next week, Inlyte plans to deliver its first battery pack to Southern Company, which operates regulated utilities in four states, at its Wilsonville, Ala., energy-storage facility.

For all of sodium-ion batteries’ strengths, there is one arena where lithium-ion batteries are still tops, owing to unavoidable physical realities: the amount of energy they can store per gram. In vehicles where weight matters, such as EVs, this means the future still mostly belongs to lithium-ion batteries.

A new race with China

China dominates production of the materials that go into today’s leading battery technologies that are based on lithium-ion chemistry, even though it was perfected in the U.S.

Without the right support from the U.S. and allied governments, the U.S. might again find itself having developed a novel energy technology, only to see China achieve a monopoly on its production, says Mukesh Chatter, CEO of Alsym Energy. Chatter’s Massachusetts-based startup is developing components that will go into sodium-ion batteries manufactured by other companies.

Chinese battery giants BYD and CATL have announced plans for industrial-scale production of sodium-ion batteries. Beijing’s capacity for long-term planning and investment gives China an advantage when trying to take nascent technologies from the prototype stage to the scale required to dominate global markets.

“We are not getting out-innovated,” says Chatter. “But it will be a shame if we get out-scaled, again.”

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Every organization has a mission, a reason for being. Organizations pass that mission — along with their terminology, procedures, systems, standards, and ways of working — to their people. People, in turn, take this context together with their own experience and work towards the mission.

Work can take many forms, from code, to documents and slides, to relationships, to outcomes in the physical world.

Some of these are straightforward: code either runs or it doesn’t. Agents have been using this feedback loop to produce code that “works” for developers over the last couple of years. But what about the rest of us?

Bringing the same leverage to the rest of the organization is a harder problem. Agents need to understand the context of the company and be able to reach the systems people use to do their jobs. They need to turn that context and access into work that moves the organization towards its mission.

That’s why we created Cloudflare OS. It gives every person an agent and workspace built around their company: how it works, what it knows, and the systems it relies on.

In May of this year, we gave every person at Cloudflare access to the first version of Cloudflare OS. Thousands of people across every function, many of them outside of engineering, use it every day to create documents and slides, automate repeatable tasks, and build small apps to visualize data and help them do their work.

Cloudflare OS also gave everyone a shared library of context and skills built by teams at Cloudflare. It captures our terminology, procedures, and best-known ways of doing recurring work as instructions an agent can follow. When one person figures out a better way to do something, everyone else can use it.

Today, we are open sourcing a new version of Cloudflare OS. Any organization can deploy it, connect it to internal systems, and make it their own.

Copy linkWhat we learned from the first version

The Cloudflare OS we are open sourcing today is based on what we learned from running the first version internally, a journey our CIO, Sam Rhea, covers in his blog post.

The first version centered on individuals working with agents through private workspaces. Apps were static rather than live software connected to internal systems, and mostly deterministic jobs still required running an agent skill again and consuming more model tokens.

Collaboration exposed a more fundamental challenge. Access to an MCP server told us which tools an agent could call, but not which underlying resources the agent had observed. Once people began sharing workspaces, apps, and outputs, we needed to ensure that collaboration could not expose information someone was not permitted to see.

We rebuilt Cloudflare OS on a new foundation to solve these problems. Security had to be part of the platform, not something every person building an app or using an agent has to implement correctly.

The result is a platform designed to belong to the company running it. You can customize the interfaces, connect your tools, and add the skills and context that capture how your organization works.

Copy linkIntroducing Cloudflare OS

Cloudflare OS starts with a conversation in your browser, like many other AI tools. What makes it different is that each conversation is grounded in the context and skills your organization has curated. Give your workspace a goal, and it can draw on that knowledge and work with the tools and data your organization already uses to achieve it.

Cloudflare OS combines three parts:

• An agent workspace grounded in context and skills your company curates, with an isolated runtime where agents can write and run code.
• A new security and governance framework for safe access to internal data and services.
• A platform for personal, modifiable apps that people can build, share, and continue changing.

What begins as a conversation can become a doc, an app, or a workflow that continues doing the work.

Copy linkAn agent workspace for everyone in your company

Agent workspaces were designed for everyone in your organization to use. You interact with them in your browser, so you don’t have to be a developer or know how to use a terminal. 

A workspace combines agent sessions, persistent state, outputs and files, resource access, and an isolated runtime where the agent can write and run code.

They come loaded with the curated context and skills your team or company has collected. No more reinventing the wheel for every task — if someone on your team has figured out the best way to do something, everyone benefits. People no longer have to explain the same process, terminology, and best practices to a model every time they start a task.

A few things you can do:

Copy linkResearch and ask questions

Ask a workspace to research a topic using company context and the resources you make available to it. The agent can write code to search, filter, join, and analyze information instead of pulling an entire dataset into the model’s context window.

Copy linkCreate docs, slides, and spreadsheets

A workspace can turn its research into a document, presentation, or spreadsheet that you can continue editing. These outputs do not have to be static files. They can remain connected to live data, be updated as their sources change, and still be exported to familiar formats or services such as Google Drive.

Copy linkCreate collaborative, connected apps for your team

When a document or spreadsheet is not enough, the agent can build an app with its own interface, logic, and state. The app can use connected company resources and support multiple people working together.

Copy linkRun deterministic workflows 

Not every job needs a full agent session. Many are a known sequence of steps with one or two places where judgment is useful. A workspace can turn those jobs into mostly deterministic workflows, using code for the predictable steps and a model only where it adds value. Workflows can run on demand, on a schedule, or when an event occurs in a connected system.

Cloudflare OS gives agents and apps governed access to systems of record through Gatekeepers (more on this in the security section below). It also supports existing Model Context Protocol (MCP) servers your organization already uses via MCP Server Portals.

Copy linkA new security and governance framework for safe access to internal data and services

As people begin experimenting with AI at work, one of their first requests is often for API keys to company systems. This makes sense: AI isn’t much use at work if it doesn’t have access to the systems people use to do their jobs.

But handing over API keys to people and agents is dangerous and does not scale. Keys often provide broad, long-lived access that is difficult to constrain, share safely, and audit.

MCP gives agents a better way to use these systems. An MCP server can hold the credential and expose a defined set of tools instead of handing the key directly to the agent. But controlling which tools an agent can call is only the first step. MCP alone does not tell us which underlying resources an agent has observed. The agent can combine information across systems, send it somewhere less restricted, or expose it through apps and outputs to people who may not be allowed to see the original resources. Authorization has to account for where the data can go next.

Copy linkAgents start with no access

Cloudflare Access controls who can enter Cloudflare OS. Inside, every agent and app starts with access to nothing. An agent can ask for access to a specific resource, which you can grant or deny. Generated code receives that resource as a typed binding:

const issues = await env.PROJECT.listIssues({
  teamId: "ENG",
  state: "open",
});

env.PROJECT is a capability representing permission to use a specific resource under a specific policy. The credential remains completely isolated from the agent and any generated code.

Server code runs in a Dynamic Worker with global outbound networking disabled. Client code runs in a sandboxed frame in the browser. Neither can reach the Internet except through capabilities you explicitly provide.

Copy linkGatekeepers govern resources and actions

A Gatekeeper is a service-specific Worker that sits between Cloudflare OS and an external service. It understands the service’s API, its resources, and the operations that can be performed on them.

Giving an agent access to your entire GitHub account is likely too broad. A Gatekeeper can give it access to a single repository, allow it to read issues but not source code, mask particular fields, apply rate limits, and require approval before merging a pull request.

The agent and its apps see a small TypeScript API. The Gatekeeper handles OAuth, holds the credential, enforces policy, records what was read, and mediates anything with an externally visible side effect.

Copy linkPolicy follows what the agent has seen

Controlling the initial read is not enough. Take, for example, the case where an agent reads a sensitive table in a data warehouse and uses it to produce a live dashboard. Sharing the dashboard must not become a way to share the table with people who could not access it directly.

Cloudflare OS records every resource agents observe. These observations remain attached to the agent and its work. When another person tries to open the workspace, interact with the agent, or view what it produced, Gatekeepers verify that person's access to the observed resources.

The same observation log is used to inform policies that determine when agents can make external requests. A read of sensitive data can prevent the agent from writing data to certain sources, inviting new collaborators, handing work to another agent, or making an outbound request.

People using agents or building apps do not have to worry about making these mistakes. The platform can now be used to handle this.

Copy linkA platform for building and sharing personal, modifiable apps

Most productivity suites give you a fixed set of applications: documents, spreadsheets, and presentations. In Cloudflare OS, each “file” can be its own application, written by an agent for one person, one project, or one team.

These are not prototypes that you have to export and deploy somewhere else. Each one is a full-stack application with client code, server code, an API, and durable state. Apps are private by default, but can be shared like documents.

Copy linkEvery app is a Worker

When you ask your workspace to build an app, the agent writes two parts:

• Client code that renders the app’s UI in the browser
• Server code that stores state and implements the app’s behavior

The server is loaded on demand as a Dynamic Worker and instantiated as a Durable Object Facet (both are features we built for this project). The facet gives the app its own SQLite database, separate from the Cloudflare OS runtime managing it. Dynamic Workers use lightweight V8 isolates, so every app can have its own isolated runtime without needing a dedicated server or container sitting around.

The browser client talks to the server using Cap’n Web, Cloudflare’s open source object-capability Remote Procedure Call (RPC) system. A server method can be called from the client like a normal JavaScript function:

const issues = await app.listIssues({
 status: "done",
});

The special part is that the agent can also call the same method.

So if you can build a tool to do a job yourself, agents can use your tool to do the job when you’re not there.

Copy linkShare the app, or share how it was built

When you build an app in Cloudflare OS, you have two ways to share them:

• Sharing your app itself lets other people collaborate in real time using the same state.
• Sharing a blueprint of your app lets other people create their own copy of your app.

An app instantiated from a blueprint contains the original app’s code. But it does not contain its SQLite data, conversation history, credentials, or connected resources. Each new app starts with independent state and resources.

This means when you share apps with your team, they can modify them themselves with AI instead of filing a feature request and assigning you.

Copy linkUse any model, and control what it costs

Cloudflare OS can be used with any model. Every inference call runs through Cloudflare AI Gateway, giving your organization one place to decide which models are available and which model should handle each job.

Not every task needs the most expensive model. You may not want to run the most expensive frontier model to summarize your unread emails every morning. AI Gateway gives you the control needed to make sure expensive models are only being used for the hardest work.

Every request is attributed to the person, team, or workspace that made it. Administrators can see where inference spend is going, set budgets and rate limits, and decide what happens when a limit is reached. 

Copy linkOpen source, so you can make it yours

Cloudflare OS is available today and is open source. Check out the cloudflare-os GitHub repository. You can deploy it into your own Cloudflare account and use your own Access policies, AI Gateway configuration, data, and integrations.

Our internal deployment reflects Cloudflare’s systems, terminology, policies, and ways of working. Yours should reflect your organization.

Cloudflare OS is designed so you can customize the interface, add internal Gatekeepers, and build organization-specific features without changing the core product.

We are releasing two repositories: the Cloudflare OS core and an example deployment based on how we run it internally at Cloudflare. The deployment repository consumes the core without patching it, providing a place for configuration, custom UI, internal integrations, analytics, and deployment pipelines.

Copy linkDelivered together with our partners

The source code is only the starting point. The context, skills, workflows, internal systems, and policies are what make Cloudflare OS even more useful for your organization.

Cloudflare’s strategic partners, Presidio and Happy Cog, will work with you to customize Cloudflare OS around how your organization operates and roll it out across your workforce.

Partners can help you curate shared skills and institutional context, build custom interfaces, connect internal systems through Gatekeepers and MCP Server Portals, and configure security, model, and cost controls.

You get your own branded Cloudflare OS, connected to your systems, running on Cloudflare, and shaped around how your people actually work.

Copy linkGet started

Cloudflare OS is available today on GitHub. You can explore the source code, try the demo, or deploy it into your own Cloudflare account in a few minutes using our starter repository.

We’re just getting started. We’re working on bringing Cloudflare OS to the Cloudflare dashboard as a fully managed product, adding containers for development workflows, and bringing workspaces into Slack and other chat tools.

If you’re interested in talking with our team, we would love to chat. Use this form to reach out!

TASHKENT/ISTANBUL -- The race to build data centers in Central Asia is intensifying, with Uzbekistan set to complete the first phase of a facility by year-end and Kazakhstan's Nvidia-backed project expected to offer 125 megawatts by 2027.

Uzbekistan's TAS-1 is backed by Saudi Arabia's DataVolt and its first plant will deliver 6 megawatts at Tashkent's IT Park by year-end. This is the first step in a plan for reaching up to 500 MW across Uzbekistan over time, as the government wants to grow the market for AI products and services to $1.5 billion by 2030.

In Kazakhstan, the Data Center Valley at Ekibastuz, a coal-mining city in the north, is aiming to eventually offer a full gigawatt, wired with 100,000 next-generation Nvidia chips. The $10 billion deal is led by U.S. AI cloud and infrastructure firm Firebird and will be many times larger than the Uzbek one.

"I would view the Firebird and Nvidia agreement as strengthening Central Asia's overall investment profile," said Aruzhan Meirkhanova, a senior analyst at research firm Outpost Eurasia. "A solid project in one country can help attract more operators, capital, suppliers, and technical expertise to the region as a whole, particularly as cooperation among Central Asian countries continues to deepen."

Indeed, money is pouring into Uzbekistan, DataVolt Chief Executive Rajit Nanda said, citing capital inflow from development finance institutions from the Gulf and Europe into the Tashkent project.

"This is true perestroika that is happening here in this country," he told Nikkei Asia in a recent interview, using the Gorbachev-era word for restructuring.

Uzbekistan still needs to attract more clients to its project. Beeline Uzbekistan, the country's mobile operator and the local arm of Nasdaq-listed telecom group VEON, has signed commercial terms to become one of the first tenants. U.S. software group Oracle has also signed a deal with the digital ministry, but both are preliminary and neither is an AI customer.

Away from this project, Uzbektelecom, the state operator, is adding data center capacity in Tashkent, Bukhara and Kokand with Japanese partners Toyota Tsusho, Internet Initiative Japan (IIJ), NEC and NTT Communications. Japan's Muroosystems Group has signed a deal for a 50-MW site meant to run entirely on small modular nuclear reactors, none of which is operating yet.

DataVolt Chief Executive Rajit Nanda says the Tashkent project uses tradable certificates as part of "greening" efforts. (DataVolt)

Kazakhstan is chasing the same prize on a different scale. The government said the Data Center Valley has drawn interest from more than 20 hyperscale companies from the U.S., China and India, and has already produced preliminary demand for over 100 MW. Neither Firebird nor Nvidia could be reached for comment.

For now, the structural advantage is with Kazakhstan. It has far larger generation capacity, cheaper power, more developed transmission and more industrial land -- the things hyperscale operators weigh first, said Sobir Kurbanov, an international development expert and fellow at Nightingale Int., an advisory firm focused on Central Asia.

The Firebird agreement widens that lead, giving Data Center Valley a more visible proposition for international anchor tenants. But Kurbanov said the contest isn't a zero-sum game.

"Uzbekistan's objective should not necessarily be to win every hyperscale investment in the next few years, but to build the strongest long-term value proposition for AI and the digital economy," said Kurbanov.

Countries will gain from an expansion of the ecosystem into cloud services, software engineering, fintech and cybersecurity, among others. Already, Uzbekistan's IT-service exports reached $940 million in 2025, while Kazakhstan's were higher at $1.14 billion.

Domestically, demand for digital services in Uzbekistan could surpass Kazakhstan's, given that its population is nearly twice that of its larger neighbor. This demand, though, must be supported by infrastructure, such as affordable power, strong connectivity and technical skills, analysts said.

The issue for both countries is that data centers need large, reliable electricity supplies, while some cooling systems also consume substantial water, resources that neither country has in abundance. DataVolt said TAS-1 will use entirely dry heat rejection, minimizing its water needs.

While there has been a drive to renewables, both countries still rely heavily on fossil fuels. Coal supplied 51.4% of Kazakhstan's electricity in 2025, while just 30% of Uzbekistan's electricity could be considered green energy, with gas covering much of the rest.

Kazakhstan's Ekibastuz offers cheaper, concentrated baseload power and greater immediate scale, but Uzbekistan offers a lower-carbon national mix and a faster renewable build-out. Operators weigh the carbon content of the power used, data-residency rules, connectivity and room to grow, and Ekibastuz's reliance on coal may deter clients with decarbonization targets, analysts said.

Firebird is building an AI factory in Armenia using Nvidia graphic processing units. (Screen grab from video on Firebird website) 

"Uzbekistan's electricity mix is currently less carbon-intensive than Kazakhstan's," Meirkhanova said. "For data center operators, however, carbon intensity is only one part of the equation."

Although DataVolt's owner Vision Invest owns a minority stake in ACWA Power, TAS-1 does not have any supply deal with the company.

Nanda said DataVolt's approach to greening the facility would be progressive and would expand over time. The facility is designed to Tier III standards, meaning it has spare power and cooling equipment ready to take over, so a unit can be serviced without worries about it going down. Backup generators are meant to ride out the outages that still hit the grid.

To improve its green credentials, DataVolt plans to use tradable International Renewable Energy Certificates -- issued for renewable electricity fed into the grid -- to match TAS-1's consumption with renewable generation hour by hour.

"The project can therefore make a credible low-carbon or transitional claim, but calling it fully green would require additional renewable capacity, storage and verifiable clean-power delivery," said Umud Shokri, a visiting senior fellow at George Mason University.

Public documents from Kazakhstan's Data Center Valley have not named any renewable certificates, clean-power contract or dedicated green supply. Kazakhstan, in fact, pitches cheap power as the draw for hyperscale tenants and casts the plan, in its own words, as "transforming Ekibastuz coal into digital export revenue."

Yevgeniya Mikhailidi is a contributing writer.