| Constellation Research

Long live on-prem data centers in the age of AI. We're serious

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

The enterprise data center was supposed to be dead by now, but the reality is on-premises workloads are getting new life courtesy of AI workloads.

That's a key take away from Constellation Research analyst Holger Mueller. In a report, "The Case for Data Centers Is Alive and Well in 2025," Mueller acknowledged the reality for on-premises infrastructure and said "workloads are not moving to the public cloud as fast as the prognosis looked a decade ago, so enterprises need to operate in a hybrid cloud environment, with critical enterprise workloads operating both in the public cloud and on-premises, in the private cloud."

Here are a few reasons why hybrid cloud is here to stay:

CxOs have to support a range of workloads. Yes, AI agents get the headlines, but enterprises are taking AI all the way to the edge. Those edge use cases are more on-prem.
Data center utilization needs make on-premises more cost effective. Performance in many regions is still better with on-prem data centers even with cloud advances.
IT operations are complex and require more heterogeneity. Data centers are a nice hedge for shifting business priorities, leverage vs. public cloud providers and budgeting (capital expenses vs. operating expenses).
Compliance is more of an issue due to large software portfolios, data residency and regulations that make data centers more attractive.
AI automation will need on-prem platforms and predictable workloads run better on data centers.

Mueller noted that every enterprise will have a different take on on-premises computing. Variables include where SAP workloads will reside, data gravity and innovation from cloud vendors vs. hardware vendors.

Bottom line: Data centers have been declared dead for years, but CxOs can see lower cost of ownership and perks as long as they keep options open with a cloudlike consumption model and can leverage high performance computing.

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HOT TAKE: ServiceNow’s Logik.ai Pick Up Signals CPQ’s Shift to Experience

Liz Miller

Vice President & Principal Analyst
Constellation Research

About Liz Miller: Liz Miller is Vice President and Principal Analyst at Constellation, focused on the org-wide team sport known as customer experience. While covering CX as an enterprise strategy, Miller spends time zeroing in on the functional demands of Marketing and Service and the evolving role of the Chief Marketing Officer, the rise of the Chief Experience Officer, the evolution of customer engagement, and the rising requirement for a new security posture that accounts for the threat to brand trust in this age of AI. With over 30 years of marketing experience, Miller offers strategic guidance on the leadership, business transformation, and technology requirements to deliver on today’s CX strategies. She has worked with global marketing organizations to transform everything from…...

Once thought of as a “seller’s tool”, Configure, Price, Quote (CPQ) solutions have shifted in recent years to be a far more robust, interactive and dynamic experiential platform. Once the domain of high-touch consumer commerce motions, and thanks to mainstay players heavily investing in the value of customer experience and sleek interfaces, CPQ has elevated the configuration experience to everything from software to services, without sacrificing the pinpoint accuracy of pricing, discounting and quoting that sellers depend on.

So, it shouldn’t be a shock that on their quest to shake up what cross-enterprise customer relationship management IS, ServiceNow has picked up the AI-forward sales and commerce CPQ darling, Logik.ai. The real question will be how quickly ServiceNow customers reimagine how they can empower selling and commerce no matter where sellers or buyers exist outside of a traditional CRM or Sales environment...and how far CPQ could reach to impact revenue in critical touchpoints like field service, service desk or contact center.

What We Know About the Deal: Not much has been revealed about the financial details of the deal. What we know is thatServiceNow has signed definitive agreement to purchase the company founded in 2021 that in January announced a year-over-year revenue growth cycle tripling in size with a customer roster of many Fortune 1000 enterprises. We also know that Logik.ai had successfully raised a $16 million in Series A (2023) and $25 million in Series B (2024) funding. Coming out the gate as Logik.io, the AI powered CPQ had been backed by the likes of Emergence Capital, Salesforce Ventures, and ServiceNow ventures…which once again has this analyst wondering just how many AI solutions ServiceNow plans on sneaking out from Salesforce. What we do know is that this won’t be the first acquisition rodeo for Logik.ai’s leadership team who hail from a very familiar name in CPQ. The deal is expected to close in mid-2025, pending regulatory approvals and closing conditions. Check out the official release, and the CR Insights on the announcement that includes thougths from my colleague covering Revenue and Growth technologies, Martin Schneider.

What Makes Logik.ai so Interesting: From the User Interface to the AI recommendations that flow across the entire experience, there is little doubt Logik.ai represents an evolution in the CPQ market. And that also should not be a surprise as the leadership team are true veterans of the space. Their deep roots into commerce-driven customer-centric experience has tell-tale heritage reminiscent of the literal OG of CPQ’s, BigMachine, acquired by Oracle and to this day one of the blueprints for experiential interfaces. For BigMachine, the experience was largely differentiated by a keen understanding that these moments of configuration were also opportunities to capture high fidelity signal from the customer. That is exactly where Logik.ai started and hasn't stopped innovating, injected a massive dose of AI and automation without leaving that heritage of experience design. For this analyst, Logik.ai had me at conversational quoting and a highly configurable rules engine, but then again, who doesn’t love saving time and focusing on the efficiency of the revenue process. But where Logik.ai gets really interesting is in its ecosystem and how that has lifted CPQ out from that traditional path of order management. With partnerships with Shopify, Adobe and BigCommerce, Logik,ai hits the ground running across multiple facets of the ServiceNow portfolio. And no…I haven’t even TOUCHED on their recently announced subscription management offerings that offer much needed relief to fast-moving commerce. So bottom line, there is a lot to like here…and a lot that can spread across the ServiceNow ecosystem.

For CX and Strategy Leaders: Yes, ServiceNow is expanding its reach and has emerged as a significant CRM player ideally suited for organizations with complex selling or commerce motions. This addition begins to round out a motion that is omnichannel on purpose, data-driven by design and intentionally leveraging the “platform of platforms” approach to AI and meaningful conversational moments that can and should beget even more meaningful moments. However, this should not be considered a single function tool or an upgrade to a selling system. That would be far too limiting and overlooks the opportunity to finally answer that age old question of how to be empower sellers in non-traditional commerce and revenue roles. In the past we’ve relied on sales and order management self service motions to empower field service to upsell or cross sell. Likewise, we’ve inserted self-service commerce modules into contact center or service desk flows that have often not connected to the customer’s actual real-time journey. What has resulted are sometimes clunky experiences where self-service is most often self-serving routing customers back to sellers and off of their prefered channel or experience of choice.

As CPQ continues to become increasingly experiential, expect to see the field deploying these commerce opportunities to not just move the revenue needle, but to also collect signal and data from customers that has proven vital to future engagement and future opportunity. For CX strategists, ask now about where and how AI tools like Logik.ai are integrated into personalization journeys. How does the signal provided directly from the customer being integrated into CRM to not just track transaction but to inform next best engagement opportunity. Does Service have access to the configuration AND the quote…or are we leaving that front line resource blind to the customer’s original intentions?

But also don’t ignore the AI and workflows that Logik.ai brings to the table…because rest assured ServiceNow has not. These aren’t just random acts of automation, but should be seen as the next evolution of what a platform of platforms is meant to curate, orchestrate and expose when putting AI to work.

Parting Thoughts: There will always be order management and quoting tools that rightly focus in on the effectiveness and efficiency of the seller’s role. These tools will set out to manaage the complexity of the selling process with an organziation. Tools that also manage and orchestrate discounts and the quote-to-cash model remain critical mainstays of the stack, and will continue to manage the complexity of financial processes. But what is important to consider here is where and how AI driven interactive CPQ tools can manage the complexity of a customer's needs and expectations. This is ServiceNow resetting the mold of how experience works and falls, to be honest, it totally in line with how Constellation Research has long asserted Customer Experience stratgegy SHOULD be viewed: as an enterprise-wide team sport that delivers durable, profitable experiences connecting buyers to brands. In this case, that strategy is decidedly interactive, driven by conversation, rich with data and silly with intentional acts of automation that hasn’t forgotten that even the most complex sales and commerce cycles shouldn’t be painful. This is about allowing CPQ to be an outside in experience tool where everybody wins.

Data to Decisions Future of Work Marketing Transformation Matrix Commerce Next-Generation Customer Experience Chief Customer Officer Chief Executive Officer Chief Financial Officer Chief Marketing Officer Chief Digital Officer

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ServiceNow acquires Logik.ai, as it steps up CRM efforts

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

ServiceNow said it will acquire Logik.ai, which specializes in AI-driven configure, price and quote (CPQ) software.

Terms of the deal weren't disclosed. ServiceNow said that the purchase of Logik.ai will expand its reach into CRM. ServiceNow said Logik.ai will also accelerate its efforts in sales and order management processes.

ServiceNow said Logik.ai will bring CPQ tools that include transaction management as well as a rules engine for deals. ServiceNow will integrate Logik.ai into its CRM and Industry Workflows, a fast growing category for the software vendor.

The Logik.ai purchase is the latest in a set of tuck-in acquisitions for ServiceNow.

Other key points about the Logik.ai purchase include:

Logik.ai features workflows for direct sales, partner, direct-to-business and consumer self-service.
Logik.ai's platform is designed to be composable so it can handle large volumes of quotes at scale.
ServiceNow was already a Logik.ai technology partner along with other companies including integrations with Salesforce, Oracle and Adobe.
ServiceNow is making a big push into CRM with its latest Yokohama release.

Constellation Research's take

Constellation Research analyst Liz Miller said:

"CPQ is an important yet sometimes overlooked part of the customer’s journey and experience. While often seen as a seller’s tool to close deals faster and quote more effectively, CPQ can deliver high fidelity signal from customers about current and future needs. With Logik.ai, ServiceNow brings on a highly configurable, API forward solution that not only ties into their CRM functionality, but could also be a valuable addition to existing service-centric offerings, bringing much needed commerce options into service environments."

Constellation Research analyst Martin Schneider said:

"The addition of CPQ capabilities to ServiceNow‘s expanding CRM portfolio adds an interesting angle, given how the company is approaching the sales side of CRM. These new capabilities will definitely build out their offerings for human-assisted sales, but also enable the ability for companies using ServiceNow to offer interesting self service options where customers can better configure the right products and services they need. These options increase customer satisfaction and reduce operation costs and streamline repeat business with less friction. Another interesting component will be how the company measures these new capabilities with its agentic AI platform to further optimize how product bundles are configured and pricing is optimized."

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The Shifting Sands of AI: Why Enterprise Leaders Need to Look Beyond OpenAI

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Dr. David Bray

Distinguished Chair of the Accelerator & Principal/CEO
Stimson Center & LeadDoAdapt Ventures

Dr. David A. Bray is a Distinguished Fellow and Chair of the Accelerator with the Alfred Lee Loomis Innovation Council at the non-partisan Henry L. Stimson Center. He is also a non-resident Distinguished Fellow with the Business Executives for National Security, and a CEO and transformation leader for different “under the radar” tech and data ventures seeking to get started in novel situations. He is Principal at LeadDoAdapt Ventures and has served in a variety of leadership roles in turbulent environments, including bioterrorism preparedness and response from 2000-2005. Dr. Bray previously was the Executive Director for a bipartisan National Commission on R&D, provided non-partisan leadership as a federal agency Senior Executive, worked with the U.S. Navy and Marines on improving…...

R "Ray" Wang

Principal Analyst and Founder
Constellation Research

R “Ray” Wang is the CEO of Silicon Valley-based Constellation Research Inc. He co-hosts DisrupTV, a weekly enterprise tech and leadership webcast that averages 50,000 views per episode and blogs at www.raywang.org. His ground-breaking best-selling book on digital transformation, Disrupting Digital Business, was published by Harvard Business Review Press in 2015. Ray's new book about Digital Giants and the future of business, titled, Everybody Wants to Rule The World was released in July 2021. Wang is well-quoted and frequently interviewed by media outlets such as the Wall Street Journal, Fox Business, CNBC, Yahoo Finance, Cheddar, and Bloomberg. Short Bio R “Ray” Wang (pronounced WAHNG) is the Founder, Chairman, and Principal Analyst of Silicon Valley-based Constellation Research Inc. He…...

A Rapidly Evolving Landscape; OpenAI's Disappearing Moat

We've been watching the generative AI landscape transform at breathtaking speed, and what concerns us most is how quickly the narrative around OpenAI has shifted from "unassailable market leader" to "company facing existential challenges." As leaders who have spent our careers at the intersection of technology, policy, and enterprise strategy, we believe that organizations making multi-million dollar AI investments need to understand the broader context beyond the marketing hype.

The concept of a "moat" in business refers to sustainable competitive advantages that protect a company from competitors. OpenAI's initial moat was built on first-mover advantage, technical superiority, and massive funding. All three pillars are now showing significant cracks.

Microsoft—OpenAI's primary backer—has began testing outside models from xAI, Meta, and even Chinese company DeepSeek. Simultaneously, Apple appears to be reconsidering its OpenAI partnership, now engaging with Google about Siri integration. These moves by two of the world's most valuable companies signal serious concerns about OpenAI's trajectory.

The technical superiority argument is also collapsing. OpenAI's rushed GPT-4.5 release shows a 30% error rate—significantly worse than both Anthropic's Claude 3.7 and xAI's Grok3. When your core product is underperforming relative to competitors, enterprise customers take notice.

Competition Is Intensifying; The Economics Don't Add Up

While OpenAI struggles, competitors are gaining momentum. Anthropic secured a $3 billion investment from Google and released Claude 3.7, which many consider technically superior to OpenAI's offerings. Elon Musk's xAI launched Grok3 with impressive deep research capabilities. Even OpenAI's former CTO, Mira Murati, launched Thinking Machines Lab and raised $2 billion at a $9 billion valuation in just two weeks.

And we can't ignore developments from China. Within the last few weeks,they announced what they described as the world's first fully autonomous AI agent, called Manus. Unlike some overhyped Western announcements, Chinese AI capabilities have generally delivered on their promises. This represents both competitive and geopolitical considerations for enterprise leaders.

The financial picture is equally concerning. OpenAI is reportedly burning through $1 billion monthly and could lose up to $44 billion by next year. Sam Altman himself admitted they lose money on every $200/month ChatGPT subscription. Their recent announcement of enterprise offerings priced between $2,000-$20,000 monthly appears to be a desperate attempt to stem these losses.

This pricing strategy reveals a company pivoting toward enterprise customers out of necessity rather than strength. But this market is already dominated by Microsoft, Amazon, and Google, who have decades-long relationships with Fortune 500 companies. OpenAI faces an uphill battle against entrenched competitors with deeper pockets and broader offerings.

Despite the recent headline-grabbing $40 billion funding round that catapulted OpenAI's valuation to $300 billion and reports that the company's revenue has grown by 30% in three months, the company still doesn't expect to break even until 2029—four years from now! This timeline raises serious questions about the sustainability of their business model, especially as they continue to burn through cash at an alarming rate.

In a telling strategic pivot, OpenAI has also announced plans to launch an open-weights reasoning model that developers can run on their own hardware. This represents a significant departure from their closed system subscription model and suggests an acknowledgment that their current approach may not remain competitive in the long term. This move appears to be a course correction in response to mounting pressure from both open-source alternatives and competitors offering more flexible deployment options.

Strategic Implications for Enterprise Leaders

For CEOs, CTOs, CIOs, and CMOs, these developments necessitate a more sophisticated approach to AI strategy. The days of simply "partnering with OpenAI" as a complete AI strategy are over. We believe enterprise leaders need to consider:

Geopolitical factors: How will US-China tensions affect your AI supply chain? What regulatory frameworks are emerging in different regions?
Economic sustainability: Are your AI partners financially viable for the long term? What happens if they significantly raise prices or pivot their business models?
Technical diversification: How can you build an AI architecture that isn't dependent on a single provider?

Enterprise clients can implement what we call a "multi-modal, multi-model" approach. This means leveraging different AI models for different use cases and maintaining the flexibility to switch providers as the landscape evolves. The companies that will win in the AI era aren't those that pick the "right" vendor today, but those that build adaptable AI architectures.

OpenAI's current valuation approaching $300 billion seems increasingly disconnected from economic reality. While they deserve credit for catalyzing the current AI revolution, enterprise leaders need to recognize that we're entering a new phase where multiple players will drive innovation.

The next 18 months will be critical. We'll see consolidation among smaller AI companies, continued heavy investment from tech giants, and potentially surprising moves from nation-states viewing AI as critical infrastructure. Enterprise leaders need to stay informed not just about the technology, but about these broader market and geopolitical dynamics.

The bottom line for enterprise leaders: your AI strategy needs to be as sophisticated as the technology itself.

Look beyond the hype, consider the full spectrum of factors at play, and build flexibility into your approach. We believe the latest "wave" of the current AI revolution is just beginning, and the winners will be those who navigate its complexities with clear-eyed strategic thinking.

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Randstad Digital: Navigating Digital Transformation, AI & Talent Solutions

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Constellation Editor in Chief Larry Dignan sat down with Renganathan at Constellation Research’s Ambient Experience Summit. Here are the main takeaways..

Digital transformation challenges remain. Companies struggle to fully leverage their digital platforms and integrate new technologies effectively, said Renganathan, an AX100 member. "Customers have invested heavily in these platforms, but they have not used the tools to its best potential,” he added.

Data quality is key to AI success. Clean, consolidated data is essential for successful AI implementation and improving both customer and employee experiences, said Renganathan. AI has been pursued heavily, but many enterprises have had to backtrack to get their data strategy down. "Data is a fulcrum. If the data is not right, then whatever the AI that you're going to implement is not going to help,” he said.

The pressure to adopt AI. There's significant board-level pressure to adopt AI, but most companies are still struggling with effective implementation, said Renganathan. "If you're not talking AI, then you will become irrelevant,” said Renganathan, who noted that there are enterprises that are struggling to put AI to work and deliver returns.

Talent and skills are challenges. Organizations need to focus on continuous skilling and reskilling to prepare for technological transformations. "Do you have the right talent or the skill set to take on projects? That's the biggest problem,” said Renganathan.

Use AI to become more agile in uncertain times. Leaders must focus on transparency, trust, and adaptability to navigate current business challenges. "We are in unprecedented times... we need to be bold. Be transparent, build trust, and ensure adaptability,” said Renganathan.

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AI’s insatiable demand for data is crushing Wikimedia’s infrastructure

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Wikimedia, the organization behind Wikipedia, said its infrastructure is being taxed by non-human traffic scraping the site for data to train AI models.

With the rise of these data collecting bots, the Wikimedia funding model is being turned upside down. Wikipedia content has been a big part of search engine results and that brought traffic to the company's site. AI has changed that equation and will challenge Wikimedia's ability to sustain itself.

In a post, Wikimedia said:

"Automated requests for our content have grown exponentially, alongside the broader technology economy, via mechanisms including scraping, APIs, and bulk downloads. This expansion happened largely without sufficient attribution, which is key to drive new users to participate in the movement, and is causing a significant load on the underlying infrastructure that keeps our sites available for everyone."

The Wikimedia experience with scraper bots collecting data to train AI models highlights another battle in the growing data access war. With large language models (LLM) already absorbing most of the world's data already, there are multiple issues revolving around infrastructure costs, API access and establishing a compensation model.

For enterprises, there will be data issues too as they try to leverage first-party data and sometimes skirmish with vendors who want to control access to their platforms by third parties. Agentic AI's biggest hurdle will be standards and charges to enable agents from different platforms to communicate, negotiate and carry out tasks. As AI develops there’s a risk that free content and data dies.

In fact, Wikimedia is paying more in infrastructure due to scraper bots downloading openly licensed images. Wikimedia said its content is free, but infrastructure isn't. Sixty-five percent of Wikimedia's most expensive traffic comes from bots.

Wikimedia said it is working on an attribution system for automated traffic so it can offer tiers for high volume scraping and API use. The company is also looking to reduce the amount of traffic generated by scrapers and the bandwidth consumed.

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Informatica adds more integration to Databricks, Snowflake, Google Cloud, AWS, Microsoft Fabric

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Informatica's Spring launch of its platform integrates its data management platform with the key enterprise data platforms as well as a preview of its CLAIRE Copilot for Data Integration.

The product launch lands as Informatica named Krish Vitaldevara, a veteran of Microsoft, Google and NetApp, is chief product officer. Vitaldevara will be paired with Bala Kumaresan, global head of engineering. Kumaresan joined Informatica earlier this year and held executive roles at Informatica, Symantec, Oracle and F5.

With its latest platform release, Informatica is connecting its data management and integration platform more with key players. Informatica is projecting 2025 revenue of $1.67 billion to $1.72 billion, or growth of 4.6% at the midpoint.

Constellation Research analyst Michael Ni said:

"While hyperscalers compete to dominate compute and data platforms race to own storage, Informatica is reinforcing its role as the trusted metadata layer enterprises depend on to govern AI at scale. Its tighter native integrations with Databricks, Snowflake, and the cloud giants don’t dissolve boundaries—they strengthen them—making Informatica the connective tissue that unifies data quality, lineage, and policy without being subsumed by expanding and increasingly complex stacks."

Here's a breakdown of some of the Informatica additions.

Data integration

Informatica launched SQL Extract Load Transform support for Databricks, Google BigQuery, Amazon Redshift and Microsoft Fabric. Informatica is adding the capability to transform data pipeline flows into SQL ELT to streamline data processing.

Private Link support for Microsoft Fabric with One Lake, Lakehouse and Data Warehouse.
Support for Apache Iceberg and Delta Lake tables with Amazon S3 storage and Hive Metastore. UniForm support for Databricks and native connector to Oracle Autonomous Database.
Preview of CLAIRE Copilot for data integration to generate data pipelines with natural language.
Unstructured data processing to identify patterns, relationships and data field types in unstructured data via CLAIRE.

iPaaS

Application integration with GenAI recipes, a set of more than 10 prebuilt packaged integration processes recipes. Recipes include Snowflake, Databricks, Google Vertex and Amazon Bedrock as well as process automation scenarios with Salesforce, Veeva, Zendesk, Shopify and others.
Application Integration runtime to scale up API and app integration.
New connectors for Google VertexAI, Snowflake Cortex, Databricks MosaicAI and Cohere. Informatica also added new messaging and application connectors.
Support for industry-specific standards for finance, securities, logistics and supply chain and aviation.
CLAIRE Copilot for iPaaS for assistance with app-to-app integrations, insights and use cases and automated object mappings.

Master Data Management (MDM) and governance

CLAIRE GPT integration for MDM to use natural language processing to search and explore metadata and data within MDM.
Match external data to MDM records without loading.
Dashboard sharing, public API enhancements and usability features.
Informatica also added governance tools with a new data access management page, automated address verification, and data access policy support for Microsoft Power BI.

Data to Decisions Chief Information Officer Chief Data Officer

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Platform9 launches community edition for Private Cloud Director

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Platform9, which has been gaining momentum in moving VMware customers to its private cloud suite, launched a community edition of its Private Cloud Director.

Private Cloud Director Community Edition, which is now generally available, has the full Private Cloud Director capabilities free of charge for single region deployments.

The goal for Platform9 is straightforward: Give enterprises a no risk way to try Private Cloud Director and get familiar with the experience. Platform9, along with Nutanix and HPE, are among the vendors targeting VMware workloads. VMware was acquired by Broadcom and although the deal was a financial hit for the vendor, customers have been vocal about pricing changes.

Platform9 Private Cloud Director has multiple capabilities that align directly with VMware. Private Cloud Director includes VM High Availability, Dynamic Resource Rebalancing, VM Live Migration, Distributed Virtual Switches and software defined networking and can be installed on existing x86 servers and existing storage.

Constellation Research analyst Holger Mueller said:

"The race for VMware replacements is on, and Platform9 is making one of the most compelling pitches as a VMware alternative, with a standards based approach, paths from VMware to Platform9 services and already a proven record with large enterrprise customers."

The community edition of Private Cloud Director, which is built on open source K3s, or production ready Kubernetes distribution, is designed for test environments on a single Ubuntu system, home labs and proof-of-concept efforts.

Platform9 has been building out its plan to reach customers as an option to replace VMware. In March, Platform9 launched its partner program to support resellers, systems integrators and managed service providers looking to replace VMware installations.

According to Platform9, it'll offer partners enablement services, high margins and performance incentives and migration services training. The company also said it is working with vendors on co-selling and co-marketing arrangements with enterprise storage vendors.

The big picture

Platform9 is putting in the building blocks to target enterprises with VMware installations and the strategy revolves around the following:

Emphasizing Kubernetes as a core pillar of the Platform9 platform and a modernization play. Kubernetes is a key consideration as companies are looking to move away from VMware, but also consider their long-term architecture.
Targeting enterprises with multiple hypervisors.
Providing VMware-like features with a more simple experience.
Highlighting deployments at scale. Platform9 has multiple large customers including Juniper Networks, Redfin and household names in telecom and retail.
Being seen as an option as enterprises need platforms that can easily move workloads seamlessly between private and public clouds.
Play the long-game since enterprises need to shift to a more modern stack over multiple years.

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AI infrastructure becomes one big leveraged bet

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

OpenAI's move to raise another $40 billion at a $300 billion valuation is being funded by Softbank, which in turn is paying for its bet with a lot of leverage.

Should we be worried about the amount of debt being floated to build out AI infrastructure? Not yet. But remember that debt is swell until it isn't.

Softbank said it will fund a $10 billion investment in OpenAI via a loan from Mizuho Bank. Softbank would wind up investing $40 billion in OpenAI in early 2026 only if the ChatGPT maker can convert into a for-profit structure.

Recall that SoftBank has already pledged $100 billion for the Stargate data center buildout with OpenAI. Softbank also recently said it would buy Ampere for $6.5 billion.

SoftBank has a long history of raising debt, scaling bets and then getting squeezed later.

Now if this were just a tale of SoftBank's debt adventures that would be one thing. But leverage is being used to fund AI infrastructure in multiple areas.

CoreWeave's IPO is another example of the power and peril of debt. CoreWeave's IPO was downsized due to concerns about it breaking debt covenants for Blackstone funding. CoreWeave stumbled out of the gate, traded below its IPO price and has just now moved ahead of the $40 mark.

The issue with CoreWeave is that it has $12.9 billion in debt commitments as of Dec. 31 on revenue of $1.92 billion. CoreWeave CEO Michael Intrator told CNBC that "debt is the engine, it's the fuel for this company."

CoreWeave rival Nebius has a bit more than $6 billion in debt.

Blackrock's AI Infrastructure Partnership push adds private equity to the mix including plans to "mobilize up to $100 billion in total investment potential when including debt financing."

This leverage bet works out great as long as AI factory demand remains insatiable. Should this demand even pause there could be debt pileups everywhere. History says this debt pileup will matter at some point.

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AWS, Amazon court developers to take Nova models for a spin, Alexa+ goes early access

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Amazon is putting its Nova family large language models (LLMs) on display for a tryout aims to spur developer interest. And if Alexa+, which is also available for early access, performs well Nova's profile will only increase.

It's no coincidence that Amazon Web Services' Nova debut is riding shotgun along with Alexa+. At the Alexa+ launch in February, Amazon noted that the upgraded voice service will be powered by Nova and Anthropic models. The architecture behind Alexa+ picks models based on the task or question at hand.

Amazon Nova's site will look familiar to anyone who has been trying out various models. You have your pick of models including Nova Pro, Nova Lite and Nova Micro as well as Amazon Nova Canvas an image generator and Nova Reel for Gallery.

The company also launched Nova Act, which is in preview and is an agent that traverse web sites and complete tasks.

Constellation Research analyst Holger Mueller said:

“Amazon/AWS are still playing with other cloud vendors. But they are narrowing the gap, and the ability of Nova to take browser actions is one of those milestones. One always has to keep in mind that Amazon is using AI to improve the customer experience of its shopping side and be able to automate browser. Actions opens totally new alleys for online retail. We will see how soon we will have these capabilities on Amazon.com and how well they work.”

At first glance, Amazon Nova appeared to be out of date. It didn't have my latest gig. The image generation was solid but lacked options.

Here's a look at an image of my dog. I asked for a watercolor, but Nova could only do some editing and provide variations. Converting to video was a nice touch.

Original image.

What Nova did with it.

Here's what OpenAI's model did with the same picture and followed up with options and was able to do a watercolor.

Nova was launched at AWS re:Invent in December and the rollout will likely include a bevy of update that will close gaps with other models.

AWS' strategy with Nova models is very similar to what it is doing with its custom silicon. The aim is to be a good enough option for multiple use cases at a lower cost. We're entering the "good enough" stage of the LLM race.

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Read more about AWS, Amazon court developers to take Nova models for a spin, Alexa+ goes early access

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