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Applied Computing wants to give oil and gas operators an AI model for the entire plant

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Applied Computing, a London-based startup that’s building a foundation AI model for the oil, gas and petrochemical industry, has raised a $20 million Series A led by engineering giant KBR, with Databricks Ventures participating.

Founded in 2023, the startup targets oil, gas, refining and petrochemical systems, where a single facility can have thousands of sensors measuring everything from temperature and pressure to velocity and viscosity. While there’s a huge market for helping energy companies solve the data tracking problem, the fragmentation that presents a significant hurdle.

Facilities consequently make operating decisions using less than 8% of the data available to them, says Applied Computing’s co-founder and CEO Callum Adamson (pictured above, right). Operators already collect much of this information, he said, but they struggle to combine the sensor readings, engineering documentation, and physics and chemistry quickly enough to analyze and make predictions.

“It’s getting those three data sources to talk to each other in real time. That’s the real key,” he told TechCrunch.

Unlike large language models, which predict the next word, Applied Computing says its foundation model, Orbital, combines a time series model, a physics-based model, and a language model to predict the state of a facility. It does this by analyzing sensor readings, keeping physics and chemistry in mind, and recognizing a facility’s equipment constraints and operator activity. It also allows technicians to run simulations of how a change in one part of a facility could affect the rest of its operations.

Image Credits:Applied Computing / Applied Computing

Essentially, Applied Computing is pitching speed: It claims Orbital can flag anomalies, investigate what caused them, and model whether a proposed fix could create problems elsewhere in the facility, all within minutes. Adamson claims the product can compress investigations that previously took days or weeks into seconds, helping operators reduce energy use and maintain output.

That promise of speed seems to have found believers. The startup says it has gone from stealth to double-digit millions in annual recurring revenue in under 18 months. Adamson said Orbital is in use at some “large, publicly listed” upstream oil and gas, downstream refining and petrochemicals companies, although he declined to mention how many customers it has.

Its partners include Indian energy company Wipro, and KBR, which has integrated Orbital into its INSITE 3.0 digital platform for energy projects, and is using the product for ammonia production. Adamson said the startup is also working with a “major U.S. upstream operator,” and plans to announce a partnership with a European oil major in the coming weeks.

Still, Applied Computing is entering a market that has entrenched industrial software suppliers as well as more focused AI startups. AspenTech sells simulation and AI-powered modeling software for upstream, refining and chemical operations, while AVEVA offers physics-based process simulation, optimization, and “what-if” modeling for industrial plants. Cognite and Seeq target the data layer, helping facilities analyze industrial data, and apply AI to design workflows.

Adamson argues that the company’s moat is not access to industrial data or process knowledge, but assembling AI researchers to build a model that can compete with Orbital. 

“It’s an AI problem. It’s not a data problem, and it’s not an energy problem,” he said. “If you’re a tier-one AI researcher, where are you going to work? … I don’t think Shell’s on that list.”

Adamson also pointed to the data Orbital receives through its deployments. Operational data from refineries and other energy facilities is generally not available publicly, he said, while simulated data cannot fully reproduce what happens inside a working plant.

The KBR partnership may help the company, too. Adamson said the partnership gives Applied Computing access to operational data, industry expertise, and also introductions to more potential customers.

Applied Computing plans to use the $20 million to expand internationally, hire for research and engineering roles, and explore deployments with energy clients.

The company on Thursday said it’s also opened an office in Houston, adding to its headquarters in London and operational hub in Bengaluru. Adamson said the U.S. base puts the startup closer to two existing customers in North America, and an expansion into the Middle East is also in the works.

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Why Greylock capped its new fund at $1.5B when it says it could have raised more

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While many top-tier venture firms keep raising massively larger funds, Greylock Ventures, one of the oldest and most prestigious venture firms in Silicon Valley, is intentionally resisting the trend of ballooning fund sizes.

On Tuesday, the 61-year-old firm announced that it had raised a $1.5 billion 18th fund. The number is 50% higher than its previous $1 billion vehicle from 2023 and roughly matches the capital the firm raised across seed and flagship funds during the pandemic. Still, Greylock partner Saam Motamedi told TechCrunch that Greylock could have easily raised a “multiple” of that figure, suggesting the partnership decided restraint was the better path at a time when fund sizes across the industry keep climbing.

“Our mission is to be the most important partner to the most important entrepreneurs,” Motamedi said. The firm prides itself on introducing its portfolio companies to top engineers and potential customers, as it did for Baseten, an AI infrastructure startup that is now valued at $13 billion, after first investing in its Series A in 2022. But Motamedi said Greylock can offer that level of support only by keeping the number of companies it backs small.

The firm’s 10 partners make only one or two new investments each annually, a pace Motamedi said will result in roughly 25 portfolio companies from this fund.

Like its predecessors, the new fund will focus primarily on incubating companies from the earliest stages and leading seed and Series A rounds. This is where Greylock has built its reputation; the firm has a strong track record of starting companies from scratch, most notably security giant Palo Alto Networks, which launched inside Greylock’s offices 21 years ago, and the email security startup Abnormal, which Greylock incubated in 2018 and that was last valued at $5.1 billion.

Even so, Greylock doesn’t stick strictly to early-stage deals. It will also back high-potential, later-stage companies even if it “missed them early on,” Motamedi said. The firm’s 17th fund included three such growth-stage bets: Anthropic, Revolut, and Wiz.

The firm made its first investment into Anthropic when the AI company raised its Series F at a $183 billion valuation. “It’s the largest investment in the firm’s history,” Motamedi said.

Motamedi estimates that roughly 15% of the new fund will be deployed into later-stage startups, but he maintains that Greylock remains fundamentally an early-stage investor.

As proof, Motamedi said that when the partners meet every Monday to review their investment pipeline, the agenda consists primarily of people’s names rather than company names.

“We’re getting to know people even before they start a company. It’s really a bet on the person,” he said. “Often the company doesn’t even exist.’”

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Microsoft is reportedly training salespeople to talk down OpenAI and Anthropic

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Microsoft appears to be prepping its sales team to get more competitive with the other major players in the AI industry.

At an internal meeting on Tuesday, the company’s executives outlined a plan for salespeople to negatively compare AI products from companies like OpenAI, Google, and Anthropic to its own, according to a new report from Bloomberg. The meeting, billed as a strategy session for the new fiscal year, reportedly leaned heavily on pitching the efficiency and cost-effectiveness of Microsoft’s in-house models against those of its rivals.

“Everyone else is selling parts — we’re selling the full end-to-end system. That’s the story that we all need to get out there and tell in FY27,” Executive Vice President Jay Parikh reportedly told the room.

Executive Vice President Jacob Andreou reportedly went further, delivering a presentation comparing Copilot directly to Anthropic’s chatbot Claude. According to Bloomberg, Andreou noted that, when it came to performance within Microsoft’s office apps, Anthropic’s model was “slower and less accurate, and lacked the proper security integrations,” Bloomberg writes.

TechCrunch has reached out to Microsoft and Anthropic for comment and will update this story if we hear from either outfit.

A company coaching its sales team on how to trash-talk competitors isn’t particularly surprising. What’s more notable is who Microsoft is now targeting — the same companies it has long depended on for the AI models powering its own products.

It’s just the latest move in that direction. A report earlier this month found that Microsoft has been swapping OpenAI and Anthropic’s models out of flagship apps like Word and Excel in favor of its own — a cost-cutting move, according to that report.

There was a time when Microsoft and OpenAI were attached at the hip. The two companies entered into a very unique agreement years ago that saw Microsoft provide capital and compute to OpenAI while allowing Microsoft to enjoy exclusive access to OpenAI’s API and models. The companies amended the partnership in April, dropping the exclusivity clause and clearing OpenAI to sell to Microsoft’s competitors.

That revised relationship may help explain the sales team’s new pitch. Microsoft has been battling a less-than-optimal stock outlook over the past year, as investors question the company’s massive spending on the buildout of its AI business. Talking up how competitive those products actually are is likely an attempt to calm those waters and build confidence in Microsoft’s long-term AI plan.

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SpaceX falls to $135 IPO price ahead of Starship launch

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SpaceX’s shares fell to just above $135 on Wednesday, the price that CEO Elon Musk and his company chose ahead of its blockbuster June 12 IPO that raked in nearly $86 billion.

The company’s stock spent much of the day below that IPO price, at one point dipping beneath $133 per share, before it traded back up to finish at $135.27.

The dip on Wednesday followed a steady decline in the month since the company went public. SpaceX initially saw its stock price rise to more than $200 in the days after it went public, briefly giving it a valuation that rivaled tech giants like Amazon and Microsoft. Its shares have lost value basically every week since reaching that high point.

Some of the volatility is attributable to the fact that just 4% of the company’s total shares are trading on the Nasdaq. That small “float,” as it’s known, combined with an immense amount of constant attention on the company, has created wild swings during the first month of trading.

The markets also appear to be sobering up on CEO Elon Musk’s grand vision for the company, part of a broader deflation in tech stocks over the last month. Not only has SpaceX’s stock traded down, but also bonds the company sold in the wake of the IPO are suffering.

A prolonged downturn for SpaceX could have wider effects because the company’s stock price is a sign of how investors view the (literal) otherworldly promises Musk has made about what his company can accomplish. SpaceX’s IPO has also set the table for other Big Tech companies like Anthropic and OpenAI to go public. Both of those companies have filed confidentially for an IPO. While neither has set a date to go public, SpaceX’s stock is being closely watched to gauge how successful those IPOs could be.

SpaceX is about to face another early test of the durability of its stock price. On Thursday the company will test launch its Starship rocket for the first time since the IPO. Starship is still very much in development, which means it is prone to failures — the result of SpaceX’s “fly, fail, fix” approach.

This will be the first Starship flight since it experienced a booster failure in May. And once again, the company does not plan to try to recover the Starship booster or upper stage on this flight, instead opting to have them simulate a landing in the Gulf of Mexico. That means both parts of the overall Starship rocket system will end in an explosion no matter what, even if they don’t run into any problems during the flight plan.

This story has been updated to include the closing price.

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