OpenAI is acquiring Tomoro, the Edinburgh-based AI consulting firm it was born alongside, as the founding acquisition of its $14 billion Deployment Company — copying Palantir’s forward-deployed engineer model to close the gap between AI capability and enterprise adoption.
TL;DR
Tomoro was created in 2023 in alliance with OpenAI. The Edinburgh and London-based firm built AI concierges for Virgin Atlantic, in-game support agents for Supercell, and deployment systems for Fidelity International, Tesco, Red Bull, Mattel, and the NBA. It grew monthly revenue tenfold in 12 months. It pledged 10 million pounds to Scottish AI talent. It employed roughly 150 forward-deployed engineers and deployment specialists whose job was to sit inside client organisations and make OpenAI’s models work in production.
On Monday, Tomoro announced it has signed an agreement to become the founding acquisition of the OpenAI Deployment Company, the 14 billion dollar subsidiary that OpenAI launched with more than four billion dollars in initial capital from 19 investment firms. The deal is subject to regulatory approval and standard closing conditions. The model company just became the services company. The AI lab that spent a decade building intelligence is now building the consulting army to install it.
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OpenAI launched the Deployment Company with four billion dollars from a syndicate led by TPG, with Advent International, Bain Capital, and Brookfield as co-lead founding partners. The remaining 15 investors include SoftBank, Goldman Sachs, Warburg Pincus, B Capital, BBVA, Emergence Capital, and consulting firms Bain and Company, Capgemini, and McKinsey. OpenAI holds a majority ownership and control stake. The structure guarantees its private equity backers a 17.5 per cent annualised return over five years.
The subsidiary exists because enterprise AI adoption has hit a wall that better models cannot fix. OpenAI’s annualised revenue reached 25 billion dollars in February 2026. Enterprise customers represent more than 40 per cent of that figure and are on pace to reach parity with consumer revenue by the end of the year. More than a million businesses use OpenAI’s products. But the gap between using a product and deploying it inside core business operations remains enormous. Model performance is no longer the bottleneck. Integration, change management, security review, evaluation harnesses, and the slow work of redesigning business processes around AI are the actual constraints.
The Deployment Company’s answer is to place engineers directly inside client organisations, partnering with those companies’ own teams to identify the highest-value opportunities and build production systems on site. The model is not new. It belongs to Palantir.
Palantir pioneered the forward-deployed engineer model over years of defence and intelligence engagements where software had to work inside institutions too complex and too classified for remote support. The company sent its own engineers directly to intelligence agencies, military clients, and later private-sector companies because its platform was nearly unusable without heavy customisation. That operational intimacy drove Palantir’s US commercial revenue to surge 133 per cent year on year, and the FDE model has been credited with generating 640 per cent returns for early investors.
OpenAI is applying the same logic to a broader market. Tomoro’s 150 engineers become the founding cadre of a deployment operation that will scale through further acquisitions funded by the four billion dollar war chest. The engineers will not sell software. They will sit inside enterprises and build the systems that make OpenAI’s software produce business outcomes. The distinction matters. A software licence is a product. An embedded engineer is a relationship. The relationship generates switching costs that no competing model can erode.
Anthropic’s own multi-billion-dollar fundraising has signalled that the AI lab model is evolving beyond research and into enterprise infrastructure. Anthropic has built a 1.5 billion dollar joint venture with Blackstone, Hellman and Friedman, and Goldman Sachs that operates as its own deployment arm. Google has committed 750 million dollars to fund partners deploying agentic AI. The three largest foundation model companies have independently concluded that the money is not in selling intelligence. It is in installing it.
Tomoro was structured from inception as an OpenAI-aligned consultancy. Its co-founders, Rishabh Sagar, Albert Phelps, Chris Spencer, Ed Broussard, Chloe Kelleher, Ash Garner, and Sandi Chanda, built the firm around a single premise: that the gap between AI access and AI deployment was a business in itself. They were right. In two and a half years, Tomoro assembled a client list that most consulting firms spend a decade building.
At Supercell, the Finnish gaming company behind Clash of Clans, Tomoro launched an in-game support agent serving 110 million users in 12 weeks. The system processes 500 million daily tokens on GPT-4o and 200 million on GPT-4o-mini across five games, reduced the cost of resolving a support ticket by 90 per cent, raised customer satisfaction scores by 20 per cent, and delivers an average response time of seven seconds. At Virgin Atlantic, Tomoro built an AI travel concierge that handles booking queries and customer service. The firm quadrupled its headcount in the 12 months before the acquisition.
Sebastian Steinhaeuser, who serves as SAP’s chief operating officer, described Tomoro in different terms last week when discussing the SAP-n8n partnership. But the Deployment Company’s own framing is revealing. Tomoro is the “founding acquisition,” language that implies it is the first of many. The four billion dollar capital base is explicitly earmarked for scaling operations and acquiring firms that can accelerate the mission. Tomoro is not the Deployment Company. It is the template.
Accenture’s stock fell three per cent on the announcement. Cognizant dropped five per cent. Infosys declined four per cent. The market’s immediate verdict was that OpenAI had entered their business. UBS maintained its buy rating on Accenture, arguing that scale advantages in legacy infrastructure, regulated environments, and geographic coverage make the two companies more complementary than competitive. The argument has merit in the short term. In the long term, it misses the point.
The consulting industry’s business model rests on a simple asymmetry: clients know less about a technology than the consultants they hire to implement it. That asymmetry is durable when the technology is complex and general-purpose, like ERP systems or cloud migration. It erodes when the technology vendor decides to close the gap itself. OpenAI is not licensing its models to consultants and hoping they deploy them well. It is embedding its own engineers inside the same clients that Accenture, Deloitte, and McKinsey serve, with deeper access to the models, faster iteration cycles, and a direct feedback loop into the next generation of capabilities.
Google committed 750 million dollars to finance agentic AI deployments through partners including Accenture, Deloitte, and KPMG, choosing to fund the existing consulting ecosystem rather than compete with it. OpenAI chose differently. It built its own. The consulting firms that invested in the Deployment Company are hedging, putting money into the entity that threatens to displace them in the hope that partnership will protect what competition would destroy.
The Deployment Company is part of a broader shift in which AI companies are vertically integrating into services. Anthropic’s joint venture with Blackstone and Goldman Sachs. Google’s partner fund. Palantir’s FDE expansion. Salesforce’s Agentforce with its 540 million dollars in annual recurring revenue and 18,500 enterprise customers. The model layer is commoditising. The application layer is fragmenting. The services layer, the part where engineers sit inside companies and make AI work, is where the margins are migrating.
Europe’s largest startup funding rounds in 2026 reflect the same pattern, with capital flowing toward companies that deploy AI inside enterprises rather than companies that build AI in laboratories. Tomoro’s journey from Edinburgh to the centre of OpenAI’s enterprise strategy is an extreme version of the trend: a consulting firm so aligned with its technology partner that the partner absorbed it entirely.
SoftBank assembled a 40 billion dollar bridge loan to fund its OpenAI investment, capital that flows through to subsidiaries like the Deployment Company and the acquisitions it will make. The financial architecture behind OpenAI’s enterprise push is not venture capital. It is private equity, structured returns, and leverage at a scale that no consulting firm can match. Accenture’s annual revenue is 65 billion dollars. The Deployment Company launched with a 14 billion dollar valuation and a mandate to acquire.
Tomoro’s own announcement was characteristically understated. “Our belief hasn’t changed,” the company wrote, “but the scale of the mission has.” The belief, as Tomoro articulated it from the beginning, is that AI should be shaped around how people think and create, redefining how work gets done. The scale is now 300,000 enterprises that OpenAI wants to convert from product users into production deployers.
The deployment gap is real. Eighty-eight per cent of organisations report using AI in at least one business function. Only a third have scaled it enterprise-wide. The distance between those two numbers is the market that the Deployment Company was created to serve. Tomoro’s 150 engineers are the first wave. The four billion dollars will fund the next. And the 17.5 per cent guaranteed return tells the private equity backers exactly how confident OpenAI is that the gap will close on its terms.
The model company built the intelligence. The Deployment Company will install it. Tomoro, the Edinburgh firm that existed for 30 months, is where the installation begins.
Few pieces of technology capture attention quite like a device that launched an era. In September 2008 T-Mobile teamed up with Google to reveal the G1, a phone built from the ground up to run Android software. Available starting that October for customers on a two-year plan, it arrived at stores priced at $179 ($277 today) and immediately drew crowds eager to try something different.
When users opened the body, they discovered a full QWERTY keyboard stashed away beneath, which was a lifesaver for hammering out emails or scribbling down quick notes without having to look for those tiny on-screen buttons. The 3.2″ capacitive touchscreen sat above the keyboard, displaying some wonderful 320 x 480 pixel pictures and menus that would come to life with a tap or sweep of the finger.
Sale
A little trackball tucked itself away just below the screen, making it easy to scroll through large lists or zoom into maps, which was difficult to perform on the glass without it. Nearby buttons handled the typical navigation, while a dedicated search key quickly returned Google results. Power came from a Qualcomm MSM7201A processor running at 528MHz and supported by 192MB of memory. In the box, they’d discover a 1GB microSD card already installed and ready to start, with room to add an 8GB one if necessary.
The 3.15MP rear camera took clear and detailed shots, and the autofocus quickly locked onto whatever you were trying to photograph. Despite the lack of a flash, daily photographs typically looked far better than you’d expect for a phone of this period. The detachable 1150 milliamp-hour battery pack provided around five hours of conversation time and more than five days on standby. It only took a few seconds to swap it out for a spare, and you were back up and running without having to find a charger.
The G1 launched with new software, the first version of Android, and did an excellent job of connecting with Google services from the start. Your Gmail would send new messages instantly, and Maps would show streets in sharp clarity and even spin to mirror the real world using a built-in compass. YouTube videos would play smoothly over Wi-Fi or a carrier data connection, and the new Android Market allowed you to download additional apps directly to your smartphone.
Connectivity-wise, the phone had all the bases covered, as it functioned on GSM networks, could do 3G speeds when available, easily snagged Wi-Fi networks, quickly paired with Bluetooth headsets, and provided accurate turn-by-turn directions via GPS. It weighed 158 grams and was just over half an inch thick, so it fit comfortably inside a pocket even with the sliding mechanism. You might choose between black, white, or brown to match your unique taste.
Pershing Square has taken a new position in Microsoft, with the size to be disclosed in a 13F filing later on Friday. The stock is down roughly 16% year-to-date.
Bill Ackman has bought Microsoft. Pershing Square’s chief executive said on X on Friday morning that the fund had taken a new position in the software company after its recent share-price decline, with the size to be disclosed in a regulatory filing later in the day.
Ackman’s stated rationale was that the market is mispricing the enterprise franchise rather than the AI one. Investors have underestimated Microsoft’s software ‘given its deeply embedded role across enterprises and highly attractive price-value proposition’, he wrote, framing the position as a quality-compounder bet on the installed base rather than a directional call on Azure capex.
The timing is the substance of the trade. Microsoft shares are down roughly 16% year-to-date and have traded near $413 since late April, when chief financial officer Amy Hood used the company’s fiscal Q3 results to raise full-year capital expenditure guidance to about $190bn, well above the roughly $155bn analysts had penciled in.
The results themselves were a beat. Azure grew 40%, the AI run-rate hit $37bn, and total revenue cleared $82.9bn. The stock fell anyway, on what one widely circulated buy-side note called the $190bn capex plan that repriced AI.
Ackman has run this play before this year. Pershing Square disclosed a new stake in Meta in February, three weeks after the latter’s own capex-driven sell-off, with Ackman describing the position at the time as a ‘deeply discounted valuation’.
The Microsoft entry follows the same shape: a megacap dragged lower by an AI-spending guide, framed by Ackman as an opportunity to buy a high-quality franchise at a temporarily de-rated multiple.
Funds running more than $100m are required to file Form 13F disclosures of US-listed positions within 45 days of quarter-end, which makes Friday a heavy day for hedge-fund reading.
Pershing Square’s last 13F, covering the December quarter, showed eleven positions and roughly $16bn in disclosed US holdings concentrated in Brookfield, Uber, Amazon, Alphabet and Meta. Microsoft did not appear. Today’s filing will show whether the firm has trimmed any existing names to fund the new one or sized it from cash.
The trade also lands inside a wider AI-infrastructure debate. Hyperscalers have committed more than $650bn to AI capex across 2026, on the combined Q1 numbers from Microsoft, Alphabet, Amazon, Meta and Apple, and the market is now pricing the question of when, or whether, that spend converts cleanly into operating earnings.
Ackman is, in effect, arguing that Microsoft’s existing Office, Windows and Azure book of business is enough to clear the bar, separately from the AI optionality.
Microsoft’s deep integration of OpenAI’s models across Copilot, Azure and the developer stack has been the dominant narrative in the company’s repricing over the past three years (TNW has tracked the arc). The capex bill is the cost of holding that lead. Ackman’s bet is that the enterprise software business underneath it is being given less credit than it should.
Pershing Square has not disclosed the size of the position or the average purchase price. The 13F filing is expected later on Friday US time.
Formerly known as WhiteHat, Multiverse was last valued at $1.7bn in 2022 following a $220m raise.
London-based edtech Multiverse has raised $70m in a round led by Schroders Capital, to accelerate its European expansion. The round places the company at a valuation of $2.1bn.
Founded by British businessperson Euan Blair, the round also saw the support of existing investors including General Catalyst, Lightspeed Venture Partners, D1 Capital Partners, Index Ventures, Bond and StepStone Group. Blair is the son of former UK prime minister Tony Blair.
Multiverse said that it wants to ensure that “AI benefits the workplace, rather than displacing it”. It was last valued at $1.7bn in 2022 following a $220m raise.
Multiverse, which was founded under the name WhiteHat in 2016, offers personalised upskilling programmes to support technological adoption. It has an AI coaching platform called Atlas.
To date, Multiverse has delivered more than £2bn worth of benefits to more than 1,000 employers, it said. Its clientele includes the likes of Microsoft, Palantir and Databricks. Atlas has tripled daily active users over the last year, the company added.
Alongside this raise, all Multiverse employees, regardless of seniority, have been offered equity and a long term stake in the company as a result of raise, Multiverse said.
“There are companies who desperately need the benefits AI can bring. There are AI companies. What has been missing is the layer that bridges the two,” said CEO Blair.
“This investment marks the moment Multiverse defines that category, and takes it across Europe. Getting outcomes from AI and unlocking productivity is not just a technology problem. It is a people problem. We exist to solve it.”
UK Chancellor of the Exchequer Rachel Reeves added: “Multiverse is a fantastic example of a British company helping turn that ambition into reality. This investment will support its expansion across Europe, strengthening a UK firm that is competing globally and equipping people with the skills to make AI work in practice.”
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Euan Blair, 2023. Image: Village Global via Flickr (CC BY-NC 2.0)
Raspberry Pi founder Eben Upton has warned AI is making people less likely to pursue tech jobs, and could therefore hurt the economy of the future.
Speaking to the BBC’s Big Boss Interview podcast, Upton said that the technology could “distort people’s choices in ways that make that skill shortage worse and not better.”
Tech layoffs have surpassed 100,000 in 2026 so far, with many attributed to companies’ usage of AI.
Upton added there is a level of overestimation of what AI chatbots can do, adding that this could “undo a lot of the good work that’s been done, not just by Raspberry Pi, but by a lot of other organisations.”
Upton founded Raspberry Pi in 2012 in order to provide an engaging way for young people to get involved in computing and programming.
Those who have built a foundational level of understanding for a tech role during their education who would then expect to further their knowledge in a place of work have found that the positions they would typically apply for are shrinking. The work that a decade ago would have been done by an entry level employee is instead handed off to an AI tool instead.
This in turn creates a self-feeding problem: how do you replace senior staff members that retire or move jobs if there isn’t a pool of talent to pick from?
Upton added his concern for parents worried about the direction their children’s education could take. “You read in the paper: ‘What guidance should you give your child about what GCSEs to choose in the context of an AI future?’ We have no data to inform a rational decision on that.”
“The answer is: wait five years, wait 10 years, and then maybe we might know something,” Upton added.
When asked if these problems could hurt the economy, Upton responded, “Absolutely. We need a supply of engineers.”
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If you happen to walk outside and unexpectedly find utility markings (paint or flags) on your driveway or in your yard, it’s good advice to heed the words splashed across the cover of “The Hitchhiker’s Guide to the Galaxy” — don’t panic, it’s not the end of the world. Next, if you didn’t call the utility company, check with your neighbors to see if one of them did, and if not, then call the nationwide 811 phone number used throughout the United States for underground utility location services, because someone is planning on doing work that might directly involve your little slice of heaven.
Most property owners probably know full well that beneath their perfectly manicured landscaping efforts lies a dizzying array of underground utility lines, irrigation systems (even those using smart controllers), and water and sewer pipes. It’s also probably safe to assume that most of us have no clue where those things are. It takes professionally trained people with the right tools to come out and locate them before anyone starts digging things up to avoid triggering a cataclysmic event. Even when professionals follow these exacting safety protocols, very bad things can still happen.
For instance, a house 15 miles south of Oakland, California, exploded in December 2025, after a construction crew hit a gas line. The house next door was also severely damaged, and six people were injured. More recently, 67 homes in Mountain View, California, were under a boil-water notice for weeks after a crew replacing the neighborhood’s water pipes allowed cement slurry to seep in, subsequently introducing bacteria into the drinking water.
For every project that involves digging into the ground – whether it’s a simple DIY effort to repair sprinkler lines, or a larger one carried out by city workers — the area needs to be inspected at least two days beforehand. Calling 811 sends utility companies out (at no charge) to locate and mark underground lines (gas, water, electric, internet, etc.) with flags and spray paint. This safety measure is a federal law meant to prevent damage to public infrastructure, personal injuries, or unwanted service outages.
The markings all have different meanings, but follow uniform color codes mandated by the American Public Works Association (APWA). Red indicates the presence of electric power lines (invented in 1882), lighting cables, and conduit. Orange means telecommunication, alarm/signal lines, cables, or conduit. Natural gas, oil, steam, petroleum, or other flammable substances will always be designated by the color yellow. Green notifies you of sewer and drain lines, while blue is for potable drinking water. Reclaimed water, irrigation, and slurry lines are represented by purple. Pink is used for temporary survey markings or things that are either unknown or unidentified. Lastly, white outlines proposed excavation limits or routes.
Utility markings should generally remain in place until the project is complete. And if you are the one doing the digging, check your state’s tolerance laws because you may need to use hand tools instead of mechanized equipment if you’re working within 24 inches of a marked line. Ultimately, it’s better to be safe than sorry, because nobody wants to be responsible for causing a problem that brands them as “that person” in their neighbor’s eyes forever.
Anduril Industries announced a massive $5 billion funding round Wednesday as the fast-growing defense tech startup ramps up investments in manufacturing and autonomous military systems — including a quietly expanding maritime operation in Seattle.
As GeekWire reported last month, Anduril established operations at the historic Foss Maritime shipyard along the southern bank of the Lake Washington Ship Canal, where the company is developing autonomous naval vessels and other maritime technologies.
The Series H funding round — including investments from Thrive Capital and Andreessen Horowitz — values Anduril at $61 billion.
The Costa Mesa, Calif.-based company said the financing will fuel aggressive investments in manufacturing capacity, R&D and infrastructure needed to produce advanced defense systems.
“When Anduril launched in 2017, defense attracted little venture investment,” CEO Brian Schimpf said in a letter, adding that investors now increasingly recognize “the scale of the technological and industrial challenges facing the United States and its allies.”
The Seattle facility underscores how the Pacific Northwest is increasingly emerging as a strategic hub for next-generation defense technologies — blending advanced manufacturing with AI, autonomy and defense software.
Just this week, GeekWire reported on Armada’s growing engineering hub in Bellevue, where the heavily funded startup is working on portable data centers for military operations and other use cases. Other Seattle-area companies such as Overland AI — autonomous military vehicles — and Echodyne — advanced radar systems — are benefitting from what CNBC dubbed a “defense tech funding boom.”
Earlier this year, autonomous vessel startup Saronic Technologies announced a $1.75 billion funding round and plans to develop a next-generation shipyard focused on autonomous naval ships — raising broader questions about where America’s future defense shipbuilding hubs will emerge.
Anduril’s expansion also lands amid renewed national focus on revitalizing America’s industrial and naval capacity. In a letter released alongside the funding announcement, the company argued that future conflicts will depend heavily on resilient production systems, rapid adaptation, and scalable autonomous technologies.
Anduril has not publicly detailed the scale of its Seattle maritime operations, and the company did not respond to requests for comment when GeekWire reported on the shipyard last month.
However, the company said in a November 2025 press release that its Seattle facility will serve as the U.S. hub for vessel assembly, integration and testing of Autonomous Surface Vessels as part of the U.S. Navy’s Modular Attack Surface Craft (MASC) program.
Anduril also is rapidly expanding its operations in California. And it is building a massive facility just south of Columbus, Ohio, that it dubs Arsenal-1, described by the company as “the future of American defense manufacturing.”
Founded in 2017 by Oculus VR creator Palmer Luckey, Anduril Industries has rapidly grown into one of the most valuable private defense companies in the world, building autonomous drones, surveillance systems, AI-powered software platforms and military robotics.
Motorola’s first book-style foldable is earning strong early reviews for its sleek design, excellent battery life, fast charging, and stylus support. Reviewers note it still lacks some of the polish of the Z Fold 7 and Pixel 10 Pro Fold, but most agree the Razr Fold is a legitimate foldable contender.
According to the researcher, YellowKey appears unusual for a previously unknown security bug. Nightmare-Eclipse explained that the flaw can be reproduced by copying an attached “FsTx” folder to a USB drive formatted with a Windows-compatible file system such as NTFS, FAT32, or exFAT.
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3D printers are almost never fast enough. [Cocoanix] had a Prusa MK3S with this very problem. He found it to be disappointingly tedious when completing even simple prints, and sought a way to make it faster. Thus, he grabbed a Nintendo Switch and got to work.
It might sound like an odd choice, and that’s because it is. There’s no special magic inside a Nintendo Switch that makes 3D printers faster – it’s just that the handheld console was a useful platform on which to run Klipper. As [Cocoanix] explains, Klipper is designed to run on faster general-purpose computers compared to the more limited microcontrollers used in some printers. It’s designed to off-load complex motion processing tasks to a faster CPU, while the printer’s onboard microcontrollers are freed up to simply handle the low-level tasks of driving the motors and so on. An older printer equipped with Klipper can often print faster, while implementing techniques like input shaping to further improve speed as well as print quality.
It’s worth noting that you don’t have to use a Nintendo Switch for this. It’s just a good hook for the YouTube video. Typically you’d use a Raspberry Pi or some other computer instead, but the fact it runs on a jailbroken console is amusing nonetheless. It’s also cool to see the results – in this video, [Cocoanix] got the Benchy printing time down from 90 minutes to just 8.
We’ve previously discussed the benefits of Klipper at length.
Samsung’s upcoming wide-screen foldable may end up making a surprising compromise in the camera department.
According to a new leak, the rumoured Galaxy Z Fold 8 Wide could launch with just two rear cameras instead of the triple-camera setup Samsung typically reserves for its premium foldables.
The device has already appeared in several leaks ahead of its expected July unveiling. This includes official-looking renders reportedly pulled from an early One UI 9 build. Those renders hinted at the simplified camera layout. Furthermore, new details from GalaxyClub and SamMobile now appear to confirm it.
According to the latest report, both rear cameras on the Z Fold 8 Wide will use 50MP sensors. The main camera will feature an f/1.8 aperture, while the secondary sensor will reportedly use an f/1.9 lens. Both cameras will also support 8K video recording at 30fps.
That setup feels fairly modest compared to Samsung’s usual foldable ambitions, and is especially notable considering devices like the Galaxy Z Fold series traditionally push heavier camera hardware.
The move also mirrors Samsung’s more experimental Galaxy S25 Edge that also adopted a similar dual-camera approach. However, unlike the S25 Edge — which features a massive 200MP primary sensor — the Z Fold 8 Wide appears to prioritise simplicity over outright camera power.
Elsewhere, the phone will include two 10MP selfie cameras, one on the outer display and another on the folding inner screen. Battery capacity may also differ from the standard model. The Z Fold 8 Wide is tipped to feature a 4,800mAh battery, slightly smaller than the 5,000mAh cell expected on the regular Galaxy Z Fold 8.
Taken together, the leaks suggest Samsung could position the Z Fold 8 Wide as a more affordable alternative within its foldable lineup. A reduced camera setup and slightly smaller battery would help explain a lower price point, especially if the company wants to make wider foldables more accessible.
The handset will also launch in several colours, with Dark Green reportedly acting as the signature finish.
Samsung is expected to officially reveal the Galaxy Z Fold 8 Wide alongside the standard Galaxy Z Fold 8 and Galaxy Z Flip 8 sometime in July.
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