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Palantir CTO: Engineering on DeepSeek 'is exquisite'

Palantir CTO: Engineering on DeepSeek 'is exquisite'

Palantir CTO Shyam Sankar said DeepSeek's latest models highlight how models are commoditizing and "the price of inference is dropping like a rock."

Speaking on Palantir's blowout fourth quarter earnings call, Sankar also said that DeepSeek also shouldn't be underestimated. Sankar said:

"One of the things I want to make sure we all do realize is that the engineering in R1 is exquisite. The optimizations that they've done are really impressive. And I don't think you can get away with the facile explanation that the Chinese just copy and we're the only innovators, we have to wake up with the respect for our adversary and realize that we are competing."

All of that said, Sankar went on to say that DeepSeek likely stole a good bit of that innovation.

"They absolutely did steal a lot of that through distillation of the models and perhaps they stole even more.

And then you can look at the GPU sales growth in Singapore. It's a tiny island nation. I'm pretty sure there's some sanction invasion going on there, and we have to realize that the AI race is winner-take-all and it's going to be a whole of nation effort that extends well beyond the DoD in order for us as a nation to win."

Another theme from the DeepSeek rise is that models are commoditizing and that'll have benefits for enterprises. However, enterprises should note that DeepSeek usage on the web goes to China for processing. If you download the model open source and work on it via a hyperscaler, the data stays put. We saw DeepSeek put through its paces side-by-side with other models and it appeared to need a good bit of tuning. 

Sankar said:

"I think one of the obvious lessons of DeepSeekR1 is something that we've been saying for the last two years, which is that the models are commoditizing. Yes, they're getting better across both closed and open, but they're also getting more similar and the price of inference is dropping like a rock. But I think the real lesson, the more profound one is that we are at war with China. We are in an AI arms race."

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Palantir US enterprise demand surges as Q4, 2025 outlook strong

Palantir US enterprise demand surges as Q4, 2025 outlook strong

Palantir delivered better-than-expected fourth quarter earnings, closed 32 deals worth more than $10 million, and gained enterprise momentum.

The company reported fourth quarter net income of $79 million, or 3 cents a share, on revenue of $828 million, up 36% from a year ago. Palantir's adjusted earnings in the fourth quarter were 14 cents a share. Wall Street was looking for 11 cents share on $799 million in revenue.

Palantir also delivered a rule of 40 score of 81%. Rule of 40 refers to a SaaS metric that dictates that a company's combined revenue growth rate and profit margin should equal or top 40%.

Alex Karp, CEO of Palantir, said the company said large language models are commoditizing and the value is more about data and ontology. "Our early insights surrounding the commoditization of large language models have evolved from theory to fact,” said Karp.

The growth for Palantir continues to come from the US and commercial sector even though its core government revenue is also strong.

In a shareholder letter, Karp said:

"This is not an incremental advance or marginal acceleration of our business. This is a new phase. We have the products and reach of an established incumbent and the speed, growth, and agility of an insurgent startup. It is that most lethal of combinations that we have been seeking to build, and the future is now coming into sharp focus. The strength of our commercial business in the United States, in particular, continues to astound even our most ardent believers."

By the numbers:

  • US revenue in the fourth quarter was $558 million, up 52% from a year ago. US commercial revenue growth was 64% and government revenue growth was 45%.
  • Palantir said it closed 129 deals of at least $1 million, 58 deals of at least $5 million, and 32 deals of at least $10 million.
  • The company ended the fourth quarter with cash and equivalents of $5.2 billion.

For 2024, Palantir reported net income of $462 million, or 19 cents a share, on revenue of $2.865 billion, up 29%. The company has continued deliver strong results and land enterprises.

As for the outlook, Palantir projected revenue between $858 million and $862 million with adjusted income of operations between $354 million to $358 million. For 2025, Palantir is projecting revenue between $3.74 billion and $3.76 billion with US commercial revenue of $1.08 billion, up at least 54%. Palantir projects GAAP net income in each quarter.

Karp in his shareholder letter continues to take a victory lap.

"We have been preparing for this moment diligently for more than twenty years. A certain indifference to the doubts and opinions of others, to the shiny and fashionable thing, was absolutely required. But our patience, and what some would fairly describe as our disregard for the received wisdom, has been rewarded."

Constellation Research analyst Holger Mueller said:

"Palantir had a good quarter, and it manages to show impressive growth rates. The 'dirty secret' is though - it is growing slower than the cloud provider growth rates. Enterprises are buying compute and storage for a 'do it yourself' approach at a higher rate than Palantir can convince them to use their platform and tools. The verdict is still out for the fiscal year if this is the toolset, professional services or both."

The power of ontology

Speaking on the earnings conference call, Karp said Palantir's approach to data ontology is its secret sauce. Ontology is what allows you to manage the LLMs to be more exact at scale.

"To get the AI to actually work in an enterprise, you have to re-segment, re-concatenate the large language models in a way where the use-case is thin enough that they can actually provide exact enough information and the concatenation of that is exact enough to provide real results in an enterprise context," said Karp. "In order to be able to teach a large language model to get more exact precise information, you would have to have a secure and clean access to the underlying data of the enterprise. No other company in the world has that kind of access like Palantir."

Ryan Taylor, Chief Revenue and Legal Officer, said the proliferation of AI models means the "raw AI labor supply is exploding." Taylor added that "while everyone else is focused on the model supply side, we're transforming AI into a measurable stream of high-value finished goods and services."

Taylor added that Palantir ability to weave LLMs into their enterprise and unlock AI leverage is helping enterprises execute faster. "Most organizations are currently stuck on the wrong side of the widening chasm, working on their two, five, and 10-year plans, which become obsolete days later failing to ever take action," said Taylor.

CTO Shyam Sankar said Palantir is in a strong position to take advantage of LLM commoditization and noted "the cost per token for inference continues to drop." The emergence of DeepSeek-R1 drove the commoditization theme home.

Sankar said:

"We viewed LLMs as a new runtime for the AI labor to capture the productive value of this AI labor, you need an intermediate representation of your enterprise that AI can actually interact with.

We are convinced the normative value for AI is enterprise autonomy, the self-driving company. Users go from performing the workflow to supervising an army of agents, teaching them how to handle edge cases and reducing 12-time, this is where we are maniacally focused with our customers."

 

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OpenAI's launch of Deep Research starts to make ChatGPT Pro subscription worth it

OpenAI's launch of Deep Research starts to make ChatGPT Pro subscription worth it

OpenAI's launch of Deep Research, an AI agent designed to create in-depth report, is the latest launch in a bid to make the $200 a month ChatGPT Pro subscription worth it.

The launch of Deep Research, a tool that can create in-depth research complete with citations, can create a report in anywhere from 3 minutes to 30 minutes.

Deep Research, assuming it can create reports that are analyst quality, could be handy for various industries in finance, academics, science and policy. It can also be handy for purchases of high-ticket items--something OpenAI notes in its blog post.

When you couple Deep Research with OpenAI Operator, which also launched on ChatGPT Pro, the $200 per month subscription starts to look more palatable based on time, or what you'd pay for an ala carte report.

OpenAI CEO Sam Altman noted that ChatGPT Pro isn't profitable yet, but the offering is young and frankly the company hasn't made the ROI case. Operator was a nice demo, but it's unclear whether it's worth the time savings.

However, Deep Research may make more sense to justify the subscription--even though I expect Google to do something similar soon.

Bottom line: You may not need lower level analysts anymore across multiple industries.

Assuming Deep Research can produce quality reports, the industries disrupted will be extensive. IT, Wall Street, legal, healthcare and other areas that deploy junior analysts won't need them. Can OpenAI Deep Research replace Bloomberg? How about that Gartner subscription? How about paralegals? Sell-side analysts on Wall Street? Management consultants? That promising college grad? Me?

OpenAI said:

"Deep Research was trained using end-to-end reinforcement learning on hard browsing and reasoning tasks across a range of domains. Through that training, it learned to plan and execute a multi-step trajectory to find the data it needs, backtracking and reacting to real-time information where necessary. The model is also able to browse over user uploaded files, plot and iterate on graphs using the python tool, embed both generated graphs and images from websites in its responses, and cite specific sentences or passages from its sources. As a result of this training, it reaches new highs on a number of public evaluations focused on real-world problems."

ChatGPT Pro users get access to Deep Research with a limit of 100 queries per month due to the reality that the model is "very compute intensive."

There is a rather large caveat worth noting.

"Deep research unlocks significant new capabilities, but it’s still early and has limitations. It can sometimes hallucinate facts in responses or make incorrect inferences, though at a notably lower rate than existing ChatGPT models, according to internal evaluations. It may struggle with distinguishing authoritative information from rumors, and currently shows weakness in confidence calibration, often failing to convey uncertainty accurately. At launch, there may be minor formatting errors in reports and citations, and tasks may take longer to kick off. We expect all these issues to quickly improve with more usage and time."

However, OpenAI is getting closer with ChatGPT Pro depending on quality. If you spend on research reports, the $2,400 a year subscription to ChatGPT Pro can be justified quickly.

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Here’s what technology buyers say about AI, technology, transformation

Here’s what technology buyers say about AI, technology, transformation

Earnings season for the December quarter and the January conference calls that follow are great for setting the scene for enterprise technology buying cycles for the year ahead.

Many of the major enterprises with multi-billion dollar technology budgets have reported earnings and with those calls come a pretty good read on the state of IT buying. Here’s a look at some choice quotes from the buy side of enterprise technology and how they’re thinking about AI, technology and transformation. These comments were taken from dozens of earnings calls in January.

The comments from CxOs highlight an optimistic view of AI and technology transformation as well as the benefits of automation. However, CxOs are focused on efficiency as well as financial prudence. 

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RTX (formerly Raytheon) CEO Chris Calio:

“We're innovating how we do our work as we continue to implement AI applications across RTX. Last year, we saw benefits in areas including product testing, first article inspections and RFP responses. For example, using Generative AI, Collins' avionics business has seen software testing cycle times improve by 3x, while maintaining our same quality standards. We have a plan this year to deploy another 40 use cases. Through our continued initiatives to leverage machine learning and generative technologies, we expect to improve operational speed, cycle times and capital utilization, while decreasing our dependency on external labor.”

T-Mobile President, Technology Ulf Ewaldsson:

"The whole network team has industrialized a process over the last years that gives the opportunity for us to dedicate towers, build up, upgrades, everything we do to exactly where customers need it. We're using AI to analyze thousands and millions of data points across the network on a daily basis to understand sentiments and movements in our customer base and correlate that with business outcomes, which is giving us the ability to allocate capital. I think what is really good with the network team now is that we are able to platformize the network using AI capabilities for an autonomous network model."

Starbucks CEO Brian Niccol:

"We're beginning to pilot a new in-store prioritization algorithm and are exploring other technology investments to improve order sequencing and our efficiency behind the counter. We're also progressing efforts that build on the strength and popularity of the Starbucks app. This includes development of a capacity-based time slot model that allows customers to schedule mobile orders and a midyear update that will simplify customization options, improve upfront pricing, and provide real-time price changes as customers customize beverages.”

Also: Starbucks aims for 4 minute barista to customer handoff process to boost CX

AT&T CEO John Stankey:

“In December, we established a new $3 billion plus run rate cost savings target that runs through the end of 2027. In 2025, we'll make progress on this goal by further integrating AI throughout our operations. We also expect to realize cost savings as we evolve our technology stacks and work to exit our legacy copper network operations across most of our wireline footprint by the end of 2029.

If you kind of look at our cost of service dynamics, a lot of that has been driven by AI tool application. And it's not that we're necessarily exclusively replacing individuals with the technology, but we're making them a lot more effective and efficient in how they handle customer needs and then complementing that with customer supported AI.

We’re also seeing demonstrative improvements in our code effectiveness. We're spending less right now to develop new code internally and getting more through the application generative AI.”

Capital One CEO Richard Fairbank:

“We’re investing more in technology and at the same time, getting all the benefits on the efficiency side, both in terms of growth and in terms of costs. Hopefully our investors share our excitement that this 700 basis point improvement that has happened since we began our tech transformation in 2013 has certainly been good. There are multiple things behind that, but the biggest driver is the technology transformation. Even as we invest a lot, there are also ways to create savings through reduced vendor costs, legacy technology and the benefits of the cloud to rebuild the company and how it operates.”

Also: CxOs upbeat on economy, plan to invest heavily on genAI, AI agents

Travelers CEO Alan Schnitzer:

“In 2024, our strategic tech investment approached nearly half of our overall tech spend of more than $1.5 billion. At the same time, our efforts to improve operating leverage also enable us to lower our expense ratio by more than 3 points, or about 10%. Broadly speaking, we're digitizing the value chain. That’s digitizing the customer journey. It's modernizing the foundation. It's advanced analytics. It's automation. It's faster speed to market, getting the right price on the risk, those sorts of things. At the enterprise level, we're also investing in talent and AI and third-party data, product development.”

Jane Fraser, CEO Citigroup:

“We accelerated our use of AI arming 30,000 developers with tools to write code and launched two AI platforms to make our 143,000 colleagues more efficient. The investments we're making to modernize our infrastructure, streamline processes and automate controls are changing how we run the bank.

We consolidated our balance sheet reporting to one unified ledger. We implemented a cloud-based solution for risk analytics to better value trading assets. We have closed out three longstanding consent orders.

We're all very focused on improving our operating expense base. Consolidating technology, the simplification work, automation, getting different utilities put in place rather than fragmented around the firm using AI tools.”

Mark Mason, CFO Citigroup:

“We spent $11.8 billion on technology, focused on digital innovation, new product development, client experience and other areas such as cybersecurity. We continue to reduce stranded costs, drive efficiencies across the businesses, and as benefits from investments in transformation and technology allow us to eliminate manual processes.”

United CEO Scott Kirby:

“We do have the leading digital team in the business. You can see in the app; you see in all kinds of places. And we have been, I think, done a Yeoman's effort, but really using genAI in all types of ways to be impactful for the airline and operations. One of the things that I'm most proud of is how much better we communicate with customers when there are delays to choice and explaining it in terms of they understand.

Another one of the interesting applications of genAI is that we have these old labor contracts that go back decades. And they've got all these provisions that have built up over decades. And you have people that have 25, 30 years of experience trying to interpret what the labor contracts mean in unusual situations. There’s literally a team of people that try to interpret and get those right, and they don’t always know. Amazingly, genAI can read the contract and give you a really good answer of what the output is.”

Also: Delta Air Lines completes cloud migration with focus on AI and data-driven customer experience

Rick Wurster, CEO Charles Schwab:

“In 2024, we invested in new technologies and capabilities that help our employees do their jobs more efficiently. We increased usage of Schwab Knowledge Assistant by 90% in 2024, which is our AI technology supporting the efficiency of our service professionals.

Through these efforts and others, we're able to drive down our cost per client account, which has decreased more than 25% in the last decade. On an inflation-adjusted basis, cost per account has decreased nearly 50%. This focus helps us keep costs low for our clients while also enabling us to invest in our highest priority growth opportunities.

In 2025, these critical efforts will continue. We'll invest in continued process transformation and systems modernization. We'll continue to invest in AI and other technology to help employees across the firm do their jobs more efficiently and free up expense capacity to fund our growth.”

Brian Moynihan, CEO Bank of America:

“Our digitalization and engagement expanded across all our businesses. We saw more than 14 billion logins to our digital platforms in 2024. Our Erica capability surpassed 2.5 billion interactions from its inception. And our CashPro app surpassed $1 trillion in payments made through the app in 2024. It's also worth noting that digital sales in our consumer product areas crossed 60% in the fourth quarter again.”

Morgan Stanley CFO Sharon Yeshaya:

"Self-funding investments remains a priority. In the short run, additional modernization efforts focused on decommissioning legacy technologies. This alongside business enabled innovation and process optimization with AI should support the firm's future efficiency path.

We've been investing in all of our processes and our systems in order to engage and make sure that we have a robust infrastructure in order to meet all of our growth objectives. And that has to do with everything across technology side, better understanding of our data, better, servicing our clients and the underlying infrastructure.”

UnitedHealth CTO Sandeep Dadlani:

“Our AI, digital, automation and modernization agenda has focused largely on removing administrative menial tasks in the system and improving consumer experiences. Some examples have been around our call center efforts. We received 10% less calls for the same consumer base compared to last year. And we haven't even scaled this fully. By the end of 2025, we will be scaling this fully, and that's one of hundreds of use cases that we are scaling.

As we focus in 2025, we are excited about more compelling consumer experiences, helping providers and clinicians with documentations and summaries, and digitizing all the paperwork in the entire healthcare experience--benefits documents, facilities, provider contracts and frictionless claims processing.”

Goldman CEO David Solomon:

“We are leveraging AI solutions to scale and transform our engineering capabilities, simplify and modernize our technology stack, drive productivity. These efficiencies will allow us to further invest for growth and improve client experience. This firm is zealously focused on its expense base and creating efficiencies that give us the capacity to invest in our franchise and grow our client franchise. We're going to continue to use technology to make the firm more productive. We're going to continue to scale and create automation of platforms.”

JPMorgan Chase CFO Jeremy Barnum:

“We're putting a lot of effort into improving the sort of ability of our software engineers to be productive as they do development and there's been a lot of focus on the development environment to enable them to be more productive. We also have a lot of focus on the efficiency of our hardware utilization.

We have probably reached peak modernization spend. Inside the tech teams, there's a little bit of capacity that gets freed up to focus on features and new product development.”

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Atlassian: A look at its system of work strategy, enterprise uptake, AI approach

Atlassian: A look at its system of work strategy, enterprise uptake, AI approach

Atlassian is exiting its second quarter on a $5 billion annual revenue run rate as its "System of Work" strategy is landing large enterprises that want to connect their technology and business teams.

The company's goal is to hit the $10 billion annual revenue run rate and its ability to leverage AI across its platform is resonating with large enterprises. Atlassian landed a record number of deals with more than $1 million in annual contract value in the second quarter.

Atlassian CEO Mike Cannon-Brookes said on an earnings conference call:

"Our cloud platform with AI threaded throughout is delivering. With more than 20 years of data and insights on how software, IT, and business teams plan, track, and deliver work, we're uniquely positioned to help teams across every organization on the planet work better together. Today, more than 1 million monthly active users are utilizing our Atlassian Intelligence features to unlock enterprise knowledge, supercharge workflows, and accelerate their team collaboration. We're seeing a number of AI interactions increase more than 25x year-over-year."

Atlassian reported a second quarter net loss of $38.2 million in the second quarter, or 15 cents a share, on revenue of $1.29 billion, up 21% from a year ago. Non-GAAP second quarter earnings were 96 cents a share, 20 cents ahead of expectations.

As for the outlook, Atlassian projected third quarter revenue of $1.34 billion to $1.35 billion with cloud revenue growth of 23.5%. For fiscal 2025, Atlassian projected revenue growth of 18.5% to 19% with cloud revenue growth of 26.5%.

The strategy

Atlassian's strategy is to expand broadly into a system of work. This work system has the potential to break down information silos and align software development, service management and work management to create what could be referred to as an alignment engine.

In a nutshell, Atlassian wants to be the system enterprises use to plan, track and execute every collaboration workflow wall-to-wall.

Here's what Atlassian's plan based on its Investor Day last year. The company said:

"As business becomes more complex, we’re seeing a rapid rise in teams like HR, marketing, and finance working with their counterparts in development and IT. Management wants to see a single system of work, teams want seamless collaboration."

This is a bit of a different spin than that work operating system category occupied by Monday.com, Asana and Smartsheet, but the efforts rhyme. Like ServiceNow, Atlassian sees its platform as something that can go well beyond software development and service management into every corporate function. In fact, Atlassian sees a $67 billion total addressable market with $18 billion of that sum sitting in its existing customer base.

Atlassian is betting it can win because its software team collaboration tools put it in a digital transformation and AI pole position. The company can also land and expand. More importantly, Atlassian has one platform where it can leverage AI across its products and 1,800 marketplace partners to extend it.

Atlassian acquires Loom for $975 million, will add asynchronous video to platform

On the product front Atlassian is doing the following:

  • Doubling down on IT service management with Jira Service Management.
  • Move its entire customer base to the cloud. In the second quarter, cloud revenue was $847 million, up 30%. Data center revenue, where Atlassian is self-managed by enterprises, was $362.3 million, up 32%.
  • Grow large enterprise accounts.
  • Layer AI and Atlassian Intelligence throughout the platform. Atlassian is in a natural position to turbo charge software team processes with AI.
  • Use Rovo, a human-AI collaboration tool that disperses knowledge to teams and their workflows to land more cross-functional enterprise teams. Rovo is Atlassian's AI agent play and it's early days in the uptake. Atlassian said customers are mostly in the Rovo proof-of-concept stage.

Atlassian launches Rovo, consolidates Jira Work Management, Jira Software | Atlassian Rovo AI additions go GA with consumption pricing on deck

Can Atlassian move upstream?

Cannon-Brookes said in a shareholder letter that 10% of Atlassian's revenue in the second quarter was from large customers. The big question on the earnings call was whether Atlassian can expand in large enterprises.

According to Cannon-Brookes, the combination of Jira Work Management and Jira Software gives the company the opportunity to touch more employees and use cases in large companies.

Atlassian is betting that large enterprises will gravitate toward platforms that can enable innovation.

Cannon-Brookes said:

"The CIOs and CEOs I speak to continue to want to form a deeper strategic relationship with Atlassian, not because of any single product we have, but because of our R&D speed, the innovation we're delivering. AI is just the latest example of that, but also the breadth of the platform, the amount of things they can see it improving from their goals all the way down to the day-to-day work that they do."

Atlassian did say there's some uncertainty in the macroeconomic environment, but the risks are manageable.

Atlassian on AI agent hype, multiple foundational models

Another item that remains to be seen is how large enterprises react to the barrage of AI agents being tossed at them. Atlassian's Rovo is also in that mix.

Cannon-Brookes was asked about the competitive dynamic in agentic AI. He had some interesting things to say.

"There's no doubt we've been through these technology transformations before. And when we go through them, you run through the hype cycle up and down, and there are certain words that mean something and then mean nothing and then end up meaning something. I think agents is probably squarely in that camp. The word is used everywhere suddenly for all sorts of things that I would argue aren't agents, but you can't control how the world uses a word."

Atlassian's definition of an AI agent goes like this.

  • AI agents have a goal, are aimed at outcomes, and have "some sort of personality."
  • They have a set of knowledge and can take action.
  • There are control parameters.
  • And AI agents actual like a virtual teammate.

"Atlassian agents are unique in that they can basically anywhere that a human being can be used in our software, an agent can do the same sorts of things. You can assign them issues, you can give them certain sets of knowledge, you can give them permission to certain actions. So that's pretty differentiated to other people who are building either a chatbot or fundamentally just something they're calling an agent," said Cannon-Brookes.

The ultimate barometer for enterprise AI vendors is the ability to pivot R&D. Cannon-Brookes said the AI market is moving quickly and vendors have to go with it.

"Our ability to build, deploy, get customer feedback and learn in a loop is really important in order to navigate these transitions," said Cannon-Brookes. "Anyone who tells you they know where this is going to be three years from now is a fool. What I can tell you is that we have to be able to learn really fast and move really fast and take the latest and greatest innovations and deploy them and get them to customers quickly. That is the best strategic path to gain that value over time."

In addition, enterprises will need vendors that rely on multiple models. Agentic AI is going to depend on a series of different models. "Atlassian Intelligence needs to be able to keep adapting modern models as fast as possible. Again, we're running more than 30 models from more than seven different vendors today. We continue to evaluate new models," said Cannon-Brookes. "It's also about all the data you have, the quality, the ability to search and ability to connect it."

"Ultimately, customers and users don't use an AI model, they use a piece of software, they use some high-level technology to interact with an agent," he added.

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Bringing Zero Trust to SAP RISE: Zscaler and SAP Partner for Secure Cloud Migrations

Bringing Zero Trust to SAP RISE: Zscaler and SAP Partner for Secure Cloud Migrations

For enterprises running legacy software on-premise, modernizing applications for the cloud is often a complex and risk-laden endeavor. One of the biggest hurdles in cloud adoption—especially in multicloud and hybrid deployment models—is security. Traditional perimeter-based security approaches are no longer sufficient to protect modern workloads, leaving enterprises exposed to rapidly evolving sophisticated cyber threats.

Recognizing the need for security to be embedded in cloud modernization efforts, Zscaler, a leader in cloud security and an SAP partner, now offers its Zero Trust Network Access (ZTNA) service natively integrated within RISE with SAP. Delivered through the Zscaler Zero Trust Exchange™ platform, Zscaler Private Access™ (ZPA™) for SAP enables enterprises with on-premise ERP workloads to migrate to the cloud securely and efficiently—eliminating the complexity and risks associated with traditional VPN-based access. 

Source: Zscaler

Why This Matters to SAP Customers

SAP RISE enables enterprises to transition from legacy on-premise deployments to cloud-based SAP solutions, helping them become more agile and competitive. However, moving mission-critical workloads to the cloud introduces new security challenges, such as securing user access, preventing lateral movement, and protecting against cyber threats in a perimeter-less environment.

Zero Trust architecture addresses this challenge. Instead of relying on network-based security models, Zero Trust enforces least-privileged access, ensuring that only authenticated and authorized users can access SAP workloads—whether they are in private data centers, public clouds, or hybrid environments. Zscaler’s integration with SAP RISE helps customers:

  • Reduce security risks by eliminating implicit trust and verifying every access request dynamically.
  • Enable secure hybrid work by allowing employees, partners, and suppliers to securely access SAP applications from anywhere without relying on VPNs or exposing networks.
  • Improve compliance and governance by ensuring consistent security policies and real-time threat protection across cloud workloads.

Zscaler’s Role in SAP RISE: How the Integration Works

Zscaler brings its Zero Trust Exchange platform to SAP RISE, offering:

  • Secure access to SAP applications: Users can securely connect to SAP workloads without exposing applications to the internet.
  • Microsegmentation and threat containment: By enforcing Zero Trust policies, the integration minimizes lateral movement risks, reducing the impact of potential breaches.
  • End-to-end visibility and policy enforcement: Enterprises can enforce uniform security policies across SAP applications, regardless of where they are deployed.

The integration aligns with SAP’s strategy of helping enterprises modernize with secure, cloud-based solutions while ensuring business continuity, resilience, and compliance.

A Step Forward in Secure Cloud Modernization

As enterprises embark on their cloud transformation journeys, security must be a foundational element rather than an afterthought. The shift to cloud-based and hybrid environments brings significant operational benefits but also introduces new security challenges that traditional perimeter-based models cannot address. A Zero Trust approach, which enforces least-privileged access and dynamic security policies, is becoming essential for protecting modern workloads.

Partnerships such as the one between SAP and Zscaler demonstrate how security can be integrated into cloud transformation initiatives, giving enterprises the confidence to modernize without compromising protection. By embedding security into migration strategies from the outset, organizations can reduce risk, improve resilience, and accelerate digital transformation with greater trust and agility. 


 

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Apple Q1 strong, but China and iPhone revenue falls

Apple Q1 strong, but China and iPhone revenue falls

Apple's first quarter results were better-than-expected as Mac, iPad and services revenue gained from a year ago. But iPhone revenue was down from a year ago as were wearables. China sales also took a hit in the first quarter.

The company, which is betting that Apple Intelligence can drive an upgrade cycle, reported first quarter earnings of $2.40 a share on revenue of $124.3 billion.

Wall Street was expecting Apple to report earnings of $2.35 a share on revenue of $124.03 billion.

CEO Tim Cook said Apple reported its best quarter ever and added that Apple Intelligence will be available in more languages in April.

By the numbers:

  • iPhone revenue in the first quarter was $69.14 billion, down from $69.7 billion a year ago. Wall Street analysts were looking for $71 billion in iPhone sales.
  • Those flattish iPhone sales come as sales in greater China for the first quarter were $18.5 billion, down 11% from $20.82 billion a year ago.
  • Mac sales in the first quarter were $8.99 billion, up 15% from $7.78 billion a year ago.
  • iPad revenue in the first quarter were $8.09 billion, up 15% from $7.02 billion a year ago.
  • Wearables revenue (mostly Apple Watch) in the first quarter was $11.75 billion, down from $11.95 billion a year ago.
  • Services revenue in the first quarter surged to $26.34 billion, up from $23.12 billion a year ago.
  • Sales in the Americas were $52.65 billion, up from $50.43 billion in the first quarter a year ago.
  • Apple saw revenue gains in Europe, Japan and the rest of Asia Pacific.

As for the outlook, Kevan Parekh, Apple’s CFO, said the stronger US dollar will be a headwind. The company expects second quarter revenue to grow in the low- to mid-single digit range.  

Cook said on the earnings conference call that Apple has more than 2.35 billion active devices. Cook was asked about Apple Intelligence and demand. He said:

"We did see that the markets where we had rolled out Apple Intelligence that the year-over-year performance on the iPhone 16 family was stronger than those where Apple intelligence was not available."

Regarding China, Cook said:

"Over half of the decline that we experienced was driven by change in channel inventory from the beginning to the end of the quarter. And on the Apple Intelligence side, we have not rolled out in China. And it's the most competitive market in the world."

Cook was also asked about cost of compute and DeepSeek's impact.
 
"In general, I think innovation that drives efficiency is a good thing. And that's what you see in that model. Our tight integration of silicon and software will continue to serve us very well. We do things on the device and we do things in the private cloud. From a CapEx point of view, we've always taken a very prudent and deliberate approach to our expenditure."

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Intel Q1 outlook light, Q4 better-than-expected

Intel Q1 outlook light, Q4 better-than-expected

Intel is still on the hunt for a CEO, but the company's fourth quarter results were better-than-expected even as sales fell from a year ago in every division except for network and edge computing.

The company reported a fourth quarter net loss of 3 cents per share on revenue of $14.3 billion, down 7% from a year ago. Non-GAAP earnings were 13 cents a share.

Wall Street was expecting Intel to report non-GAAP fourth quarter earnings of 12 cents a share on revenue of $13.83 billion.

The financial report was the first since Pat Gelsinger retired as CEO in December to be replaced by co-CEOs David Zinsner and Michelle (MJ) Johnston Holthaus.

Intel reported a 2024 loss of $18.8 billion, or $4.38 a share, on revenue of $53.1 billion, down 2% from the previous year.

As for the outlook, Intel said it will report first quarter revenue of $11.7 billion to $12.7 billion with breakeven earnings per share on a non-GAAP basis. Wall Street was looking for non-GAAP first quarter earnings of 9 cents a share.

Holthaus, who is also CEO of Intel Products, said the fourth quarter was a "positive step" and the company is simplifying its portfolio. Zinsner, who is also CFO, said the first quarter outlook "reflects seasonal weakness magnified by macro uncertainties, further inventory digestion and competitive dynamics."

By the numbers:

  • Intel's Client Computing Group fourth quarter revenue was $8 billion, down 9% from a year ago. Intel said it is on track to ship more than 100 million AI PCs by the end of 2025.

  • The Data Center and AI unit delivered fourth quarter revenue of $3.4 billion, down 3% from a year ago.
  • Network and Edge had revenue in the fourth quarter of $1.6 billion, up 10% from a year ago.
  • Intel Foundry revenue in the fourth quarter was $4.5 billion, down 13%.

 

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Oracle scales Oracle Database@Google Cloud

Oracle scales Oracle Database@Google Cloud

Oracle and Google Cloud said the companies will add eight new regions for Oracle Database@Google Cloud.

The companies also said they will add new features including the including the general availability of cross-region disaster recovery and database replication for Oracle Autonomous Database Serverless on Oracle Database@Google Cloud. Support for single-node Oracle database deployments on Oracle Exadata Database Service on Dedicated Infrastructure for Oracle Database@Google Cloud is also added.

Oracle's cloud, AI plans are a master class in co-opetition

Oracle and Google Cloud announced a partnership last year with plans to scale up rapidly.

According to the companies, Oracle Database@Google Cloud will add more regions over the next 12 months including:

  • U.S. Central 1 (Iowa)
  • North America-Northeast 1 (Montreal)
  • North America-Northeast 2 (Toronto)
  • Asia-Northeast 1 (Tokyo)
  • Asia-Northeast 2 (Osaka)
  • Asia-South 1 (Mumbai)
  • Asia-South 2 (Delhi)
  • South America-East 1 (Sao Paulo).

Oracle said it will double capacity in Google Cloud regions in London, Frankfurt and Ashburn.

Constellation Research analyst Holger Mueller said:

"Oracle keeps doubling down on what works--and that is putting its Exadata machines in other cloud vendors' data centers. It is good news for customers who can keep using their database with the tools and AI they want to use. It is good news for both vendors as they generate cloud revenue. The reprieve on R&D from not having to build a highly scalable transactional RDBMS (at Microsoft and AWS, lesser at Google Cloud) is the R&D angle to this development."

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DOJ sues to thwart HPE's acquisition of Juniper Networks

DOJ sues to thwart HPE's acquisition of Juniper Networks

The Department of Justice sued to block Hewlett Packard Enterprise's planned acquisition of Juniper arguing that the combination will hamper competition in the enterprise wireless networking market.

In a statement and lawsuit, the DOJ said:

"HPE and Juniper are successful companies. But rather than continue to compete as rivals in the WLAN marketplace, they seek to consolidate — increasing concentration in an already concentrated market."

HPE announced the acquisition more than a year ago. The DOJ argument is that the combination of HPE and Juniper along with Cisco will represent 70% of the wireless local area network market. According to the DOJ complaint, HPE couldn't beat Juniper's Mist AI capabilities so it chose to acquire its rival.

HPE said the DOJ lawsuit "is fundamentally flawed" and an "overreaching interpretation of antitrust laws." HPE said that its networking portfolio is complementary to Juniper's products. The company said:

"The DOJ’s claim that the WLAN market is composed of three primary players is substantially disconnected from market realities. As customers shift to AI and cloud-driven business strategies for secure, unified technology solutions to protect their data, barriers to entry have decreased and expansion and competition for WLAN has intensified. As such, WLAN is an extremely competitive market with a broad set of players, all of whom are fighting for business and winning bids in competitive RFP processes. The transaction will not impede the ability of other WLAN vendors to vigorously compete."

HPE also noted that its proposed acquisition of Juniper has been approved by antitrust regulators in 14 jurisdictions including the European Union.

Constellation Research analyst Holger Mueller said:

“If anybody would have thought that the Trump administration would be more lenient on M&A – here is the counterproof. A dominant position in the WLAN market Is far from being achieved but given the bad track record of tech enterprises have in lawsuits with the DOJ, this is not good news for HPE investors.”

 

 

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