Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Nvidia said its GB200 NVL72 rack scale systems outperformed Hopper by a wide margin based on MLPerf Training submissions across categories.

The company outlined the benchmark as its Blackwell instances--GB200 NVL72--are now generally available from Microsoft Azure, CoreWeave and Google Cloud with more providers on deck.

Nvidia was the only platform that submitted for all benchmarks including the new Llama 3.1 405B pre-training test. Nvidia was also out to show the benefits of its complete stack with fifth-gen NVLink and NVLink Switch delivering 2.6x more training performance per GPU compared to Hopper.

• Nvidia Q1 strong, continues to ride data center demand
• Nvidia launches NVLink Fusion to connect any CPU with its GPU, AI stack
• Nvidia NeMo Microservices generally available, aims for AI agent data flywheel
• Nvidia GTC 2025: Six lingering questions
• Nvidia launches DGX Spark, DGX Station personal AI supercomputers
• Nvidia launches Blackwell Ultra, Dynamo. outlines roadmap through 2027

Here's a look at the results, which can be found at Mlcommons.org, which oversees MLPerf Training metrics. MLPerf was developed by MLCommons Association to create a standard benchmark for AI workloads. The results are peer reviewed.

In a 2023 presentation on Hopper performance, Microsoft Azure was predominantly featured. This version of MLPerf Training performance was more about the AI factory. Constellation Research analyst Holger Mueller said:

"Nvidia once again has shown that it provides the best multi-cloud and on premise AI architecture for all three critical training use cases – pre-training, post training and test time scaling. Adoption across cloud and hardware vendors remains impressive. Apart from Oracle, the big three cloud providers are not part of the current Nvidia presentation. Microsoft Azure was a key feature back in fall of 2023. It is too early to overinterpret any of these changes in the presentation – but all three major cloud providers also provide their inhouse AI chip architectures."

The AI factory strategy

The MLPerf Training metrics are just part of Nvidia's overall AI Factory strategy. Nvidia CEO Jensen Huang has repeatedly argued that AI factories are a trillion-dollar opportunity that will replace traditional data centers. Every company will eventually have an AI factory to power operations.

According to Nvidia, AI factories will generate revenue as we move to a token-based, data economy. The job for Nvidia is to build that optimal integrated stack of GPUs, compute, networking and storage to efficiently scale to gigawatt AI factories. Nvidia's ultimate mote is likely to be its application stack that features everything from models, AI agents, digital twins and an enterprise suite.

These AI factories will come in four flavors: Cloud, enterprise, sovereign AI and industry-focused.

Nvidia will need to show performance gains annually to justify its annual cadence for AI infrastructure. Here's what's on tap.

• Blackwell (2025): Current generation with GB200 and GB300 variants
• Rubin/Rubin Ultra (2026): Next generation
• Kyber (2027): Future architecture
• Fineman (2028): Long-term roadmap

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Hewlett Packard Enterprise delivered better-than-expected second quarter earnings as it saw strong demand for its AI servers and hybrid cloud.

The company reported a second quarter net loss of 82 cents a share due to a goodwill write down. HPE reported second quarter non-GAAP earnings of 38 cents a share on revenue of $7.6 billion, up 6% from a year ago.

Wall Street was expecting HPE to report second quarter earnings of 33 cents a share on revenue of $7.5 billion.

HPE's first quarter results fell short of expectations and the company has delivered less AI growth than Dell Technologies. See: Dell Technologies continues to ride AI infrastructure wave with strong Q1

CEO Antonio Neri said, "in a very dynamic macro environment, we executed our strategy with discipline." CFO Marie Myers said the company is focused on streamlining operations and meeting its guidance for fiscal 2025.

By the numbers:

• HPE server revenue in the second quarter was $4.1 billion, up 6% from a year ago.
• Intelligent edge revenue was $1.2 billion, up 7% from a year ago.
• Hybrid cloud revenue was $1.5 billion, up 13% from a year ago.

As for the outlook, HPE said third quarter revenue will be between $8.2 billion to $8.5 billion with non-GAAP earnings of 40 cents a share to 45 cents a share. For fiscal 2025, HPE said revenue growth will be 7% to 9% in constant currency with non-GAAP earnings of $1.78 a share to $1.90 a share.

Constellation Research analyst Holger Mueller said:

"HPE had a solid quarter growing across its offering portfolio. Management decided to ‘hide’ the solid numbers with an impairment charge of the goodwill of its hybrid cloud portfolio, painting the quarter red. It feels more like a strategy to prepare for better quarters and take the charge now. The pressure on Q3 and Q4 will rise. The 2% average higher discounting should not come as a surprise in times of higher uncertainty and more challenging economic conditions."

Neri said the following on HPE's second quarter earnings call:

• "Through focused and disciplined execution, we have addressed the operational challenges we experienced in our Server segment last quarter. We expect these actions will contribute to margin improvement through fiscal year-end."
• "The IT industry continues to navigate significant uncertainty brought on by tariffs, the AI diffusion policy withdrawal and broad macroeconomic concerns. While this led to uneven demand during the quarter, we did not benefit from significant order pull-ins. We ended Q2 with a stronger pipeline compared to Q1."
• "I want to reinforce our commitment to closing the Juniper Networks transaction. We expect the proposed transaction will deliver at least $450 million in annual run rate synergies to our shareholders within 36 months of closing the transaction. The deal will help both companies deliver a modern secure AI-driven edge-to-cloud portfolio of networking products and services. We continue to expect to close the transaction before the end of fiscal year 2025."
• "We reduced inventory by $500 million. We believe that the remaining actions will be addressed through the back half as we convert more revenue. In Q3, we're going to convert a very large deployment that we expect to be completed here soon."
• "A third of our orders in AI being now enterprise driven. So that's a very strong momentum there. It's driven by our servers."

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

CrowdStrike delivered mixed first quarter results and second quarter outlook.

The company reported a first quarter net loss of $110.2 million, or 44 cents a share, on revenue of $1.1 billion, up 20% from a year ago. Non-GAAP earnings were 73 cents a share.

Wall Street was expecting CrowdStrike to report non-GAAP earnings of 66 cents a share on revenue of $1.11 billion.

As for the outlook, CrowdStrike projected second quarter revenue of $1.14 billion to $1.512 billion. Wall Street was looking for $1.16 billion in revenue for the second quarter. Non-GAAP earnings for the second quarter will be 82 cents a share to 84 cents a share. For fiscal 2026, CrowdStrike projected $4.74 billion to $4.8 billion with non-GAAP earnings of $3.44 a share to $3.56 a share.

The company said it authorized up to $1 billion to buy back shares, which are now up more than 58% from a year ago.

Despite the results that disappointed Wall Street, CrowdStrike delivered a strong quarter. CEO George Kurtz said the company started the fiscal year with a large deal and saw strong net retention. "The scale of Falcon Flex demand and the pace of innovation across AI, next-gen SIEM, cloud, identity, and exposure management advances us towards $10 billion in ending ARR," said Kurtz.

CFO Burt Podbere said CrowdStrike was seeing customers consolidate on Falcon Flex and the company had a strong pipeline for the second half of fiscal 2026.

Kurtz said the following on the earnings conference call:

• "In less than 2 years since starting Falcon Flex, we've closed more than $3.2 billion of total account deal value across more than 820 accounts that have adopted the subscription model."
• "A lot of what we're doing with customers is going through the demand plan and our business value assessment, and that's really where we can talk about how we can replace other point products. So typically, the conversation will look at customer road map. They'll look at certainly our road map and the products we have in the 30 modules. And then we'll begin to plan the phased rollout of our products to replace what they have."
• "When we think about generative AI and really, what I'd call autonomous agents, they have the same needs, but they're superhuman. They have access to data. They have identities. They have access to systems outside of their own environment. They have workflows. They take action. So it's building those guardrails and then instrumenting the visibility and protection across the entire AI workflow. And every agent, and there could be billions of agents, are going to need protection."

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Ciroos raised $21 million to deliver an agentic AI teammate for AI, DevOps and operations teams to automate and cut incident response times by 90%. What's interesting about Ciroos is that it is looking to address gaps in observability and its approach wouldn't have been possible without agentic AI.

The company is looking to solve a big problem for site reliability engineers (SREs)--it's almost impossible to keep up with operations across multiple applications, domains, architectures, and tools, including static runbooks and dashboards. And as enterprises move to AI agents, keeping up with operations is even more challenging. Energy Impact Partners led the funding.

Ronak Desai, co-founder and CEO of Ciroos, said the company built its AI SRE Teammate to "end the toil" for SREs by accelerating root cause identification, automating actions, and giving back time and control to build reliable systems.

Ciroos is betting that it can reimagine observability operations with its AI SRE Teammate to start investigations into anomalies before an expert is paged. Ciroos is using a multi-agent system that correlates data and uses reasoning to identify what is and isn't a problem for operations. According to the company, Ciroos's SRE Teammate supports Modern Context Protocol (MCP) and Agent 2 Agent (A2A) architectures and will integrate with existing observability applications, ticketing systems, collaboration tools, code repositories, and incident response tools.

The company, founded in February by Desai, Amit Patel, and Ananda Rajagopal, has a strong pedigree. Desai was the senior vice president and general manager of Cisco's Observability and AppsDynamics unit and also led Cisco's Cloud Networking Engineering. Patel, CTO of Ciroos, was vice president of engineering at Cisco AppDynamics. Rajagopal, chief product officer at Ciroos, was vice president of product at Cisco AppDynamics and held leadership roles at AWS, Gigamon, and Brocade.

Here are the takeaways from my chat with Desai.

What's the vision for the company? "We're building an AI SRE Teammate to help our operations teams," said Desai. "If you think about modern ID infrastructure, and you have to investigate outages, there are hundreds of experts that need to get involved with lots of tools and dashboards. It takes, on average, two hours to resolve. Ciroos wants to end all of that and give the time back."

He added that the goal is to reduce investigation time to minutes with agentic AI across multiple domains, a vast amount of data and take action with human-like reasoning.

Start with solving a problem. Desai saw the SRE challenges upfront at Cisco's data center group. "I would hear from enterprise customers saying they have lots of tools and in some cases hundreds of tools, not counting security," said Desai. "There's a siloed way of looking at tools and dashboards without correlated insights. If you think about what's happening with AI coding tools and developer productivity, the same thing can happen for SREs."

Once reasoning models became popular, it was clear that Ciroos could solve for cross-domain correlation problems. "The ability to solve that problem with the technology it was a perfect combination for us to get started," said Desai. "What we're doing wouldn't have been possible just using early large language models of 2023 and 2024."

Where Ciroos fits. Desai said its main competition is manual labor, more than existing observability tools. "We do not compete with any of the observability tools," said Desai. "We are competing with manual labor and the toil SREs have. They are looking at hundreds of dashboards and trying to figure everything out and the cognitive load is too much for humans. We're going after that problem and still keeping humans in the loop."

Desai said the Ciroos can bring SREs hundreds of experts to provide insights ready for them when they are woken up at 2 am. Ciroos's SRE Teammate is designed to automate and speed up investigations and proactively investigate issues. "We want to give SREs all the information they need, the root cause analysis and implement remediation," said Desai.

Integrations. Desai said Ciroos SRE Teammate integrates the ecosystem of tools across observability, incident management and ticketing to extract the right set of information from logs, metrics, tracing, and events. "When your human SRE expert gets on the call to investigate an incident, they’re looking at not only historical data but all the signals connected to the live system," said Desai. "We're putting all of that information into a reasoning model that can narrow down problems and determine what's critical."

ROI. Desai quipped that sleep is the best measure of uptime for SREs. "We're really looking to avoid that manual toil and the tasks which we do not want our human SREs to do," said Desai. Cutting down on narrowing down the problem, war room calls, dashboard diving, and time for investigations is the real ROI. The goal is to cut long investigation windows down to minutes.

Extensibility. Ciroos will be built to leverage whatever new advances in models. Cirooswill also be extensible as a way to adapt to new technologies. "Out of the box, we built into agent-to-agent capability where we can hook it into an agent that the customer has deployed or developed on their own," said Desai. "We are working with open and extensible ecosystems so we can work with what the customer's environment is."

What's next? Desai said Ciroos is building out its product for a launch soon and working on its agents with customers as well as inviting other early adopters. The company is also building out multi-domain knowledge for the platform. "The goal is to reduce human toil from SREs so that we can give them the sleep and time back and build a scalable system," said Desai. "We're focusing on the problems that matter to enterprises."

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Snowflake launched a bevy of data and AI enhancements that position the company as "an agent of transformation."

The combination of launches at Summit 2025 highlight how Snowflake is expanding its lens for its platform ranging from analytics to data to AI. CEO Sridhar Ramaswamy said the company's revised mission statement is to "empower every enterprise to achieve its full potential through data and AI."

The big theme at Snowflake Summit 2025 is about stitching together data sets, tools and workflows to enable AI use cases. "Snowflake is where data does more," said Ramaswamy, noting the conference's mantra.

Ramaswamy noted that Snowflake is in a different place than it was a year ago due to strong results and a faster product cadence. "Over the past few years, we've been expanding our lens. Obviously, we started as an analytics platform, but we've been adding substantial functionality to that platform, extending it so that we can work with customers. We can help customers through more of their data life cycle," said Ramaswamy.

According to Ramaswamy, Snowflake is in a place where it can bring together AI and unstructured and structured data. Here's a look at the major announcements from Snowflake Summit 2025.

• Snowflake makes its Postgres move, acquires Crunchy Data
• Snowflake delivers strong Q1, Q2 outlook
• Snowflake adds OpenAI models to Cortex AI via expanded Microsoft partnership, integration
• Snowflake, Anthropic ink LLM partnership, delivers strong Q3, acquires Datavolo

Snowflake Adaptive Compute, platform enhancements

Snowflake announced the addition of Adaptive Compute to is data warehouse platform. The company also outlined Standard Warehouse-Generation 2 with 2.1x faster analytics performance over the previous generation, interoperability features and AI security and governance features in Snowflake Horizon Catalog.

Here's the breakdown:

• Snowflake Gen2 warehouses are retooled with upgraded hardware and enhanced software and generally available.
• Snowflake Adaptive Compute, which is in private beta, automatically scales resources and routes queries efficiently behind the scenes. Customers won't have to manually manage warehouse sizes, concurrency settings and multi-cluster configurations. Adaptive Compute will power Adaptive Warehouses.
• Snowflake Chief Product Officer Christian Kleinerman said this adaptive compute approach eliminates complexity from the platform. "We're bringing increased ease of use to the platform," said Kleinerman. "We are materially improving the price performance of the platform of Snowflake."
• Gen2 warehouses feature simplified conversion to adaptive warehouses without downtime.
• Interoperability across catalogs and engines with Catalog-Linked Databases, which will enable customers to automatically sync Snowflake Horizon Catalog with Apache Iceberg objects managed by any Iceberg REST Catalog including Apache Polaris and AWS Glue.
• Expanded Data Discovery with Universal Search, which is in private preview. Customers will be able to discover data in external relational databases including Postgres SQL, MySQL without leaving Snowflake.
• Pfizer was cited as an early adopter of Adaptive Compute.

AI-Driven data governance, security and compliance including the ability to ask security questions via Snowflake Cortex AI as well as a set of AI observability tools.

Snowflake Openflow

The company launched Snowflake Openflow, which simplifies the movement of data to where it can be used. Openflow is the evolution of Snowflake's Datavolo acquisition.

Snowflake said Openflow is a multi-modal data ingestion service that will give users the ability to connect any data source and architecture.

Openflow, which is powered by Apache NiFi, will enable customers to meld data engineering practices into their Snowflake workflows.

With Openflow, Snowflake is pursuing what it calls limitless interoperability to create data that's ready for AI uses. Openflow has multiple integrations with Box, Google Ads, ServiceNow, Workday and Zendesk to name a few.

Snowflake Intelligence, Data Science Agent

At Snowflake Summit 2025, executives also moved to outline how the company is leveraging AI for customer use cases and democratizing data for business users.

The company launched Snowflake Intelligence, which will be in public preview soon, to offer users a conversational experience with data agents that can traverse dashboards, structured and unstructured data stores and analytics tools to deliver answers.

In a demo, Snowflake showed how users in different functions--finance, marketing, manufacturing--could ask questions and run SQL queries without analysts and technical expertise in a compliant manner.

Snowflake Intelligence leverages the platform's connectors, Openflow and Cortex Knowledge Extensions that can bring in third party content from Snowflake partners.

According to Snowflake, Snowflake Intelligence uses large language models from Anthropic and OpenAI running inside Snowflake perimeter with Cortex Agents.

Snowflake also launched Data Science Agent, which will be in private preview. Data Science Agent automates machine learning model development tasks, and AI workflows to boost productivity.

Data Science Agent uses Anthropic's Claude model to break down problems into steps including data analysis, data prep, feature engineering and training.

Cortex AISQL, SnowConvert AI

Snowflake launched Cortex AISQL, which embeds generative AI into customer queries to analyze and build pipelines with SQL syntax. Snowflake claimed that Cortex AISQL can lead up to 60% cost savings when filtering or joining data.

According to Snowflake, Cortex AISQL can "effectively turn every data analyst into an AI engineer." Cortex AISQL uses models from Anthropic, Meta, Mistral and OpenAI and combines them with Snowflake's SQL Engine.

The secret sauce for Cortex AISQL is that analysts can query both structured and unstructured data to analyze multi-modal data, eliminate silos, consolidate tools and enrich customer tables.

SnowConvert AI is designed to make data warehouse, business intelligence and extract transform and load (ETL) migrations faster. Snowflake said SnowConvert AI makes code conversion and testing phases in migrating from legacy systems 2x to 3x faster.

Snowflake Marketplace enhancements

Snowflake launched Cortex Knowledge Extensions on Snowflake Marketplace to add content and data from The Associated Press, CB Insights and Stack Overflow. These third-party content partners can be used to enrich AI apps with real-time news.

Via Snowflake Marketplace, customers can share Semantic Models to integrate AI-ready structured data within their Snowflake Cortex AI apps.

Snowflake also rolled out Agentic Snowflake Native Apps on Snowflake Marketplace. Agentic Native Apps are interoperable and can deliver standalone experiences on customer or provider data or be used as building blocks for apps created on Cortex Agents or in Snowflake Intelligence.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

UKG said it has acquired Shiftboard, which provides employee scheduling software for oil and gas, energy and manufacturing companies.

Terms of the deal weren't disclosed. Shiftboard brings customers such as BASF, Bridgestone, Daisy Brand and Shell to UKG.

Scheduling for Shiftboard's industries requires operational continuity and engagement with predominantly frontline workers. Shiftboard's software orchestrates scheduling, labor strategy, production demand and various union and regulatory requirements.

According to UKG, Shiftboard's industry employee scheduling platform will be integrated into UKG Pro Workforce Management suite and UKG's AI experiences and insights. Shiftboard already had integrations with UKG as well as Workday, SAP, ADP, Microsoft Dynamics and others.

The deal is notable considering UKG was formed in 2020 via the merger of Ultimate Software and Kronos. Since that combination, which formed UKG, the company has made a series of cloud acquisitions including EverythingBenefits, Great Place to Work, Ascentis, SpotCues and Immedis.

UKG also recently forged a partnership with ServiceNow to integrate AI agents.

Last year, UKG named Jennifer Morgan CEO. Morgan had been co-CEO of SAP. Since Morgan joined in July 2024, UKG has revamped the leadership team. UKG has added a new CFO, Chief Product Officer, Chief Marketing Officer, Chief Communications Officer, CIO and Chief Partner Officer.

Holger Mueller, an analyst at Constellation Research, said UKG's acquisition counters ADP in the emerging category of fatigue management in human capital management. Mueller said:

"Less than 2 weeks ago at UKG's global industry analyst conference I asked what is the future of the many vertical scheduling engines that primarily includes Kronos, but also systems Ultimate had collected through the decades. Now we know. Acquire innovative startups that bridge more industries - in this case regulated industries, where there are additional than legal requirements, e.g. fatigue management and more. This is a smart move by the new UKG leadership team. Now comes the hard work of consolidating scheduling engines."

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Snowflake said it will acquire Crunchy Data, which provides open source Postgres technology, and launch Snowflake Postgres for its AI Data Cloud.

Terms of the deal weren't disclosed, but the Wall Street Journal put the price tag at about $250 million. Databricks acquired Neon, a startup offering similar Postgres services for $1 billion.

Snowflake's acquisition of Crunchy Data kicks off the company's Snowflake Summit 2025. Databricks' conference is next week as the fierce rivals battle for data workloads used for AI applications.

• Snowflake delivers strong Q1, Q2 outlook
• Snowflake adds OpenAI models to Cortex AI via expanded Microsoft partnership, integration
• Snowflake, Anthropic ink LLM partnership, delivers strong Q3, acquires Datavolo

Crunchy Data will bring FedRAMP compliant products directly into Snowflake Postgres and Snowflake AI Data Cloud. PostgreSQL is a popular database for developers and that popularity has extended to agentic AI. Vivek Raghunathan, SVP of Engineering at Snowflake, said in a statement that Crunchy Data addresses "a real need for our customers to bring Postgres to the Snowflake AI Data Cloud."

In a blog post, Snowflake noted that Crunchy Data has built a strong following making Postgres enterprise friendly and mission critical with offerings that "span managed cloud services, Kubernetes deployments and on-premise solutions." Crunchy Data also recently launched a Postgres-native data warehouse with Iceberg support.

According to Snowflake, the company will make a strong commitment to Postgres as well as existing Crunchy Data customers. Snowflake said Snowflake Postgres, which will be available in private preview, is part of a strategy to support transactional data along with efforts like Unistore.

Constellation Research's take

Michael Ni, an analyst at Constellation Research, said:

"Databricks bought Neon. Snowflake countered with Crunchy. This isn’t about big data analytics anymore—it’s about becoming the AI-native data foundation unifying analytics, operational storage, and machine learning. Crunchy gives Snowflake an enterprise-grade PostgreSQL engine to support AI agents, co-pilot apps, and context-aware workflows that demand structured, compliant, and low-latency operational data storage. This is about turning insights into action without leaving the Snowflake platform."

Constellation Research analyst Holger Mueller said: 

"If one had any doubt that PostgteSQL is the common denominator for accessing data outside of the large commercial databases, then this move by Snowflake removes those doubts. The acquisition further cements the position of PostgreSQL as the lingua franca for accessing data. It is good to see Snowflake and other vendors supporting the query language."

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Pegasystems launched Pega Agentic Process Fabric, a service that aims to orchestrate AI agents and make them more reliable with process knowledge.

The launch, outlined at PegaWorld, builds on Pegasystems strategy to combine agentic AI and its core workflow and process platform. For instance Page Agentic Process Fabric is an extension of the Pega Process Fabric, which enables agents, apps, systems and data to coordinate.

Pegasystems applications are designed for everything from business process management to customer engagement and digital process automation. Those areas all intersect with what AI agents will do and have led to strong demand for Pegasystems' Pega GenAI Blueprint. Pegasystems' growth has surged as enterprises look to leverage AI tools without additional risk on a platform that's known well.

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Speaking on Pegasystems first quarter earnings call, CEO Alan Trefler said Pega GenAI Blueprint has been in "pretty much every client conversation we have." He noted that Blueprint serves as an AI agent that uses Pega's best practices and melds it with customer data and workflows to build applications.

He added:

"Enterprises want the promise and power of automation that agents could offer, but we don't think they want thousands of agents running unchecked, producing unreliable, undesirable results. They need an agent to wherever possible follow a consistent process with full transparency on how it does work out. And this is where our unique approach is, combining the power of language model-driven agents with the predictability of workflows."

Trefler noted that PegaWorld has more than 200 live demos of its agentic AI meets process automation approach. The company's headline products are Pega Infinity, Pegasystems' suite, and Pega Blueprint, which use generative AI and best practices to create application workflows and automation.

Pega Agentic Process Fabric features the following:

• The ability to analyze its library of discoverable agents, workflows and data across systems to find AI agent is best suited for the task.
• Workflow tools that extend Pegasystems Pega Predictable AI Agents to combine workflows and AI reasoning. When Pega Agentic Process Fabric invokes a workflow, Pega Predictable AI Agents interact with users on guided compliant workflows.
• Support for Model Context Protocol (MCP) and Agent-to-Agent (A2A).
• Security controls to prevent misuse.

Pega Agentic Process Fabric will be available in the third quarter as part of its Pega Infinity suite. The company said several parts of Fabric are available now.

Here's a look at Pega Infinity.

Pegasystems delivered strong revenue growth in the fourth quarter due to is Pega GenAI applications. The company reported first quarter net income of $85.42 million on revenue of $475.63 million, up 44% from a year ago. Non-GAAP earnings of $1.53 a share were well ahead of expectations.

Constellation Research analyst Liz Miller said:

"While the market has been talking about Agentic AI and overloading buyers with a laundry list of AI agents, bots and orchestrators, Pega has been focused on the underlying processes and workflows that have long been their bread and butter. Their approach to AI has been rooted in predictability and responsibility, and this new step forward with agentic AI capabilities is no different. "

The company also announced the following at PegaWorld.

• Pega Infinity App Studio gets agentic AI tools for developers to speed up design, integration, user experience and testing. Pegasystems added an enhanced AI developer agent, integrations between Pega applications and third party systems and a new design agent for robotic process automation. Pega Infinity App Studio leverages Pega Blueprint, an AI-driven workflow designer.
• AI agents in Pega Blueprint can ingest, analyze and convert legacy system assets to aid modernization efforts. AI agents on Pega Blueprint will also deliver process insights on legacy systems and analyze and generate information needed to build a data model that can help move apps to the cloud.
• Systems integrators will be able to use Pega Blueprints to integrate their own intellectual property with the Pegasystems knowledge base.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

HCLSoftware launched HCL Unica+, the latest version of its marketing platform featuring a bevy of AI agent features.

For HCLSoftware, HCL Unica+ represents an effort to future-proof the marketing stack. HCL said it has reimagined Unica+ to be AI first and meld intelligence, intention and data to add context and insights to what customers want.

Raj Iyer, Executive Vice President and Portfolio Manager, HCLSoftware, said the goal of HCL Unica+ is to create a "bridge to trust" where digital experiences are personalized and leverage intent to strengthen relationships. HCLSoftware bills Unica+ as the "MarTech Platform for the Intelligence Economy."

Constellation Research analyst Liz Miller said HCL Unica+ is an effort to make customer engagements more intentional. She said:

"The age of random applications of AI, automation and data is over as customers and marketers alike have heightened expectations for engagement rich with intentionality and notable outcomes. CMOs and their teams deserve marketing technologies that meet this new era of intelligence head on with platforms that deliver context and understanding of both the customer and the business, drawing from data and insights from across the organization and across the digital and physical reality of the customer."

Research: B2B Marketing for the Enterprise: HCL Unica | Constellation ShortListâ„¢ B2C Marketing Automation for the Enterprise | Constellation ShortListâ„¢ B2B Marketing Automation for the Enterprise

Features of HCL Unica+ include:

• A set of autonomous AI agents including Segmentation Agent, which produces personalized offers, Content Optimizer Agent, which automates content for contextual engagement, and Insights Agent, which manages campaign performance.
• MaxAI Workbench, which gives teams the ability to build custom AI models for campaigns and audience scoring. MaxAI is an assistant designed to efficiently design, refine and execute marketing strategy.
• Digital Body Language, which is a tool to read digital behavior and gauge intent.
• Real-time personalization, which optimizes messaging.
• Customer One view, which unified customer data into one profile.
• Guardrails for privacy, compliance, safety and responsible AI.

The launch of HCL Unica+ will be followed up with a webinar Tuesday June 3. Iyer and Dario Debarbieri, Chief Marketing Officer, outlining and demonstrating the new features.

Here are a few screenshots of HCLUnica+: