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

Google said its Gemini 2.5 Pro and Gemini 2.5 Flash now run natively in Databricks and can be run using SQL, Python and Databricks tools.

According to Google, Gemini models will run natively via an integration between the Databricks Intelligence Platform and Google Cloud's Vertex AI. The general idea is to run Gemini models where data resides. The companies announced a partnership in June.

Key points:

• Teams can apply Gemini models to their data with Batch Inference.
• Developers can build AI agents with Agent Bricks and connect them to private data.
• Use real-time APIs for high-intelligence models.
• Access Gemini models with compliance, governance and observability.

Google noted that Gemini models on Databricks via SQL or Python is designed to simplify the process for applying large language models (LLMs) to enterprise data. Use cases include automating tasks like contract analysis, parsing PDFs, summarizing transcripts and classifying images.

The Gemini offerings are generally available.

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

AMD reported better-than-expected third quarter results as its data center unit delivered revenue growth of 22% and its PC sales grew 46% from a year ago.

The chipmaker reported third quarter earnings of $1.24 billion, or 75 cents a share, on revenue of $9.246 billion, up 36% from a year ago. Non-GAAP earnings in the quarter were $1.20 a share.

Wall Street was expecting AMD to report non-GAAP earnings of $1.17 a share on revenue of $8.75 billion.

AMD CEO Lisa Su said the quarter was fueled by "broad based demand for our high-performance EPYC and Ryzen processors and Instinct AI accelerators."

By the numbers:

• Data center sales in the third quarter were $4.3 billion, up 22% from a year ago, with strong demand for 5th Gen AMD EPYC processors and AMD Instinct MI350 Series GPUs. Data center operating income was $1.07 billion.
• Client and gaming revenue was $4 billion in the third quarter, which was up 73% from a year ago. Client revenue was $2.8 billion, up 46% and gaming revenue was $1.3 billion, up 181% from a year ago. AMD said sales of Ryzen processors and Radeon gaming GPUs were strong. Operating income was $867 million.
• Embedded revenue was $857 million, down 8% from a year ago, with operating income of $283 million.

During the quarter, AMD inked deals with multiple hyperscalers as well as OpenAI.

As for the outlook, AMD said fourth quarter revenue will be about $9.6 billion, give or take $300 million, or revenue growth of 25% compared to a year ago. The outlook doesn't include revenue from AMD Instinct MI308 shipments to China.

The company will hold an investor day next week with more details on AMD's straetgy. AMD's Su said the following on the earnings call. 

• "It's a pretty unique time for AI right now. There's just so much compute demand across all of the workloads. With OpenAI, we are planning multiple quarters out, ensuring that the power is available, and that the supply chain is available. The key point is the first gigawatt we will start deploying in the second half of '26 and you know that work is well underway," said Su.
• Interest is strong for AMD's Helios designs and MI450 AI accelerators. "I think the interest in Helios has just expanded over the last number of weeks, certainly with some of the announcements that we've made with OpenAI and OCI," said Su.
• "Given what we see today, we see a very good demand environment into 2026," said Su.
• "AMD commercial PC momentum accelerated in the quarter with rising PC sell through up more than 30% year over year, as enterprise adoption grew sharply, driven by large wins with Fortune 500 companies across healthcare, financial services, manufacturing, automotive and pharmaceuticals."

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

Perplexity said it "received an aggressive legal threat from Amazon" demanding it prohibits its Comet browser users from using AI assistants on Amazon. Get used to similar kerfuffle.

Agentic AI is going to uproot a lot of well-established models. Commerce will likely be one of the larger categories disrupted. In Perplexity's blog, the company accused Amazon of being a bully, but the reality is we're in uncharted territory. Is an AI assistant the same as a human shopper (probably not)? Should an AI agent be valued like a human relationship (probably not)? Will AI agents mean an overall decrease in impulse buys? And can AI agents step in the middle of the customer relationship in commerce (probably)?

All of these questions will have to be answered along with business arrangements on the back end.

You can read Perplexity's somewhat overwrought post yourself, but the big picture is this:

• Perplexity says AI agents represent the user like a human assistant would.
• "Your AI assistant must be indistinguishable from you,"
• Agentic AI could empower users but could also be a tool to shape commerce traffic (ads too for that matter).
• The real beef is over who will have the power.

During Shopify's third quarter earnings call, President Harley Finkelstein riffed on AI agents and commerce.

"Put simply, AI is able to fundamentally change how we shop, moving from search to conversation, helping all consumers purchase more efficiently. And that's why we built the Commerce for Agents tools that we introduced on our last call, Catalog, Universal Cart and Checkout Kit. These tools make it easier for agents to shop across merchant stores on a buyer's behalf.

But here's the thing. Agentic commerce is so much more than just the last click. Think about it in 3 layers: product discovery, purchasing experience and the post-purchase journey. Now if you're only looking at the payment or checkout layer, you're missing the bigger picture of what we're building: a seamless and intuitive shopping experience end to end."

Finkelstein noted that Shopify is well positioned because it has the data behind the commerce transaction. It has structured data across billions of products and can surface relevant items in second. As shopping becomes more conversational, it's more personalized. Shopify has teamed up with OpenAI's ChatGPT as well as Perplexity.

Finkelstein said:

"Once a shopper finds what they want, Universal Cart and Checkout Kit make add to cart and checkout seamless inside the conversation. ChatGPT, along with Microsoft Copilot have already partnered with us here to make in-chat shopping flows possible.

And finally, post purchase. We're investing in tools that help agents keep customers engaged and informed, order status, return, support, reorder prompts, so the experience stays smooth and merchants build durable relationships with their customers. Of course, different permutations will emerge as agentic commerce evolves, and we are preparing our merchants to be well positioned for whatever path wins."

Commerce is a huge category and the battles are just beginning. What remains to be seen is who owns the keys to the data as well as the funnel.

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

SAP advanced its plans for developer tools, SAP Build, the Joule roadmap and connecting to a broader ecosystem including a partnership with Snowflake.

At SAP TechEd 2025 in Berlin, the company outlined a series of AI-driven tools in SAP Build as well as a set of Joule Agents designed to enable developers to move faster.

Muhammad Alam, a member of the Executive Board at SP, said the innovations at SAP TechEd create a "unique flywheel of applications, data and AI put developers in the driver’s seat."

Specifically, SAP outlined the following:

• Developers who use agentic AI platforms such as Cursor, Claude Code, Cline and Windsurf can now use SAP frameworks via SAP Build local Model Context Protocol (MCP) servers.
• Visual Studio Code users will be able to use SAP Build via extensions.
• The extension will be available later on the Open VSX Registry.
• Joule Studio will get new tools to customize SAP ready-to-use agents as well as build new ones grounded in SAP business data.
• SAP rolled out new Joule AI assistants to coordinate multiple agents across workflows, departments and applications for finance, supply chain and HR.
• The company partnered with Snowflake on a new SAP Snowflake extension for SAP Business Data Cloud. The partnership gives joint customers the ability to move data bidirectionally.
• SAP HANA Cloud knowledge graph ending can now automatically generate knowledge graphs.
• SAP launched its first enterprise relational foundation model, which is focused on business outcomes. SAP-RPT-1, short for the first-generation Relational Pre-trained Transformer, can make predictions for common business scenarios including delivery delays and payment risk.

• SAP Q3 mixed, outlook for 2025 at low end

Constellation Research analyst Holger Mueller said the SAP TechEd lineup was compelling. He said:

"SAP delivered a compelling keynote, showing how the SAP product teams work together for customer success on AI, application development and more - which was not always the case and good to see. With innovations on the Joule, SAP's agentic framework, advances on SAP Business Data Cloud, language driven and vibe code based development, ABAP models coming to on premises customers, SAP has shown significant innovation dynamic for its customer base. The question now is will it help SAP customers to tackle the task at hand - the upgrade to S/4HANA Cloud."

Here are the key points from Alam at SAP TechEd. 

App–Data–AI Flywheel & ROI

• SAP’s thesis: Real ROI comes from the seamless integration of applications, data, and AI, rather than isolated AI experiments.
• SAP’s business suite spans finance, supply chain, HR, CRM, and more, giving it an advantage in creating a “global maximum” of value versus “local optimizations” seen in siloed systems.
• Embedded AI in unified applications enables automation and insight across end-to-end business processes.

Assistants, Agents, and Human Productivity

• SAP envisions AI as an assistive layer first—to make people smarter, faster, and more efficient—before evolving toward autonomous execution once trust is built.
• Example: demand-planning and supply-planning agents collaborating autonomously across functions.
• The “assistant” concept begins with human-in-the-loop confidence building, leading later to autonomous operations when maturity allows.

AI Hype vs. Real ROI

• AI hype has inflated expectations. Many companies now realize value only comes from simplifying and structuring the equation—embedding AI in core workflows, not generating random apps.
• 95% of firms once reported no ROI (MIT study), but a newer study found 74% now see positive ROI—mainly those that adapt workflows and culture rather than just bolt on AI.
• ROI perception varies: executives tend to report success, managers often don’t see it yet.

SAP’s Approach to AI Value Creation

• SAP focuses on incremental AI adoption—enhancing existing roles and processes rather than replacing them.
• Companies should start by making core roles (like AR clerks or billing agents) more efficient, then progress toward autonomous execution.
• AI maturity follows a staged “value journey”: assistive → semi-autonomous → autonomous → deep research.

Developers, Product Managers & the AI Workforce

• SAP employs ~40,000 developers but sees enough backlog for 200,000 developers’ worth of work—AI helps scale output, not replace people.
• AI agents are multiplying productivity (7x–12x) in some teams by automating code generation, testing, and design.
• SAP Build and Joule Studio Agent Builder will let developers and customers create AI agents in low-code/no-code environments.
• Roles like product manager, QA, UX, designer will evolve but not disappear—AI will change team ratios and workflows.

Data Ecosystem & Partnerships

• Business Data Cloud (BDC) launched in 2025 integrates with Snowflake and Databricks, allowing zero-copy data sharing.
• SAP aims for open, governed, interoperable data management, letting customers combine SAP and non-SAP data seamlessly.

Organizational Design & Industry Collaboration

• SAP is experimenting with “Dev Games of the Future” to rethink team structures and collaboration models for AI-augmented development.
• Emphasis on evolving from people upward, not top-down reorganization.
• SAP collaborates with large customers and institutions (e.g., Linux Foundation) on defining future role structures and standards.

ROI Beyond Headcount Reduction

• SAP stresses AI ROI doesn’t equate to layoffs—it’s about growth, productivity, and redeployment of talent.
• Customers view AI as a tool to expand capacity, not shrink the workforce.

Accountability & Measurement for AI

• ROI and accountability come from embedding AI in structured business processes where performance can be measured (e.g., sourcing contracts closed, savings achieved).
• SAP’s new Agent Topology Index maps and tracks agents (SAP and non-SAP) to measure outcomes and performance signals.

Quantum Computing Outlook

• SAP is experimenting with quantum computing but sees it as post-2030 for commercial rollout.
• Quantum will serve different use cases than AI, likely focusing on performance and optimization problems.

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 Snowflake Intelligence to general availability, outlined a set of new developer tools and forged a pact with SAP so Snowflake AI Data Cloud and SAP Business Data Cloud are interoperable.

The company said Snowflake Intelligence, outlined at Snowflake Summit earlier this year, is now generally available. Snowflake said that Snowflake Horizon Catalog and Snowflake Openflow, also announced at Snowflake Summit, are also generally available.

Snowflake Intelligence is designed to create agents that can operate via natural language, leverage structured and unstructured data and accelerate AI and machine learning pipelines. Customers embedded in Snowflake Intelligence include Cisco, Fanatics, Toyota Motor Europe and Wolfspeed.

• Snowflake launches Agent GPA, aims to grade your AI agents
• Snowflake, Palantir forge data integration partnership
• Snowflake launches Cortex AI for Financial Services, MCP Server
• Snowflake, Salesforce, BlackRock lead effort to standardize semantic data

According to Snowflake, prebuilt agents can be accessed through the Snowflake Intelligence interface or using Cortex Agents API. Cortex Agents orchestrate unstructured and structured data with LLMs including OpenAI GPT and Anthropic Claude.

Snowflake also outlined a suite of new development tools that feature a collaboration environment, open source integrations and data quality capabilities.

The developer tools include:

• Cortex Code in private preview. Cortex Code is a revamped AI assistant in the Snowflake interface and helps customers understand usage, optimizations and fine tuning.
• Enhancements to Snowflake Cortex AISQL, which is generally available. Developers can build AI pipelines in Snowflake Dynamic Tables.
• Snowflake Workspaces for collaboration and direct Git Integration and VS Code Integration.

Under the SAP-Snowflake partnership, the companies said Snowflake's data and AI platform will be available as an extension for SAP Business Data Cloud. SAP launched Business Data Cloud via a partnership with Databricks.

SAP and Snowflake will enable the following:

• Zero copy sharing between the two platforms.
• Data and AI teams can work within a unified governance framework and harmonize SAP and non-SAP data.
• Simplify AI governance, ground AI in enterprise knowledge bases and build tailored agents.
• Leverage semantically rich data.
• SAP Business Data Cloud can leverage Snowflake's AI, analytics, data engineering, marketplace and collaboration tools.

In addition to SAP Snowflake solution extension for SAP Business Data Cloud, the companies said the partnership includes SAP Business Data Cloud Connect for Snowflake, which enables bidirectional, zero copy data sharing. SAP Snowflake will be available in the first quarter with SAP Business Data Cloud Connect landing in the first half of 2026.

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 is looking to give your AI agents a GPA. While the company is grading the accuracy of AI agents, it's really evaluating goals, plans and actions (GPA) in an open source framework that reaches near human levels of error detection rates and localization accuracy.

The framework, called Agent GPA, was outlined at its Build conference. For enterprises deploying agentic AI, Snowflake's efforts are worth a look.

In a blog post, Snowflake's AI Research team said evaluating AI agents comes down to trust. Snowflake said:

"An agent’s answer may appear successful, but the path it took to get there may not be. Was the goal achieved efficiently? Did the plan make sense? Were the right tools used? Did the agent follow through? Without visibility into these steps, teams risk deploying agents that look reliable but create hidden costs in production. Inaccuracies can waste compute, inflate latency and lead to the wrong business decisions, all of which erode trust at scale."

Snowflake argued that current evaluation frameworks fall short because they focus on the final answer, not the process behind the answers. Here's a look at the Agent GPA framework. Agent GPA, outlined in a paper, is available in Truelens.

Snowflake's Agent GPA was the headliner among a set of items released by the company's research team.

Other items include:

• Text-to-SQL V1.5, a specialized model that fuels Snowflake Intelligence, Snowflake's enterprise agent, by tackling the slowness, cost, and dialect issues of general LLMs. The specialized model makes text-to-SQL queries up to 3 times faster while maintaining accuracy.
• New optimizations will be introduced for Cortex AISQL, a tool that integrates AI directly into SQL queries, enabling teams to analyze all data types and build flexible AI pipelines using familiar SQL syntax.
• The Cortex AISQL enhancements improve AI operator efficiency and cost, featuring 2-8x more performant execution plans, 2-6x faster inference (at 90-95% accuracy), and a 15-70x reduction in execution costs and time through techniques like cost-aware optimization, adaptive model cascading, and query enhancements.

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

Celonis is looking to embed its process intelligence platform into agentic AI workloads and make it clear that AI agents sans process knowhow won't deliver enterprise value.

At Celosphere 2025 in Munich, Celonis outlined the following:

• Celonis Process Intelligence additions that integrate data lakes without data duplication, tools to build more comprehensive digital twins of enterprises and blueprints for enterprise architecture.
• A partnership with Databricks that integrates Delta Sharing to directly connect the Celonis Process Intelligence Platform with the Databricks Data Intelligence Platform.
• And enterprise value use cases from the likes of Mercedes Benz, Uniper, Vinfast and 120 other "value champions" that have realized value of more than $10 million each.

Alex Rinke, co-CEO of Celonis, said the company is looking to help enterprises get value from their AI investments. "We give their AI the context it needs. We guide them to deploy it in the right places. And we enable them to make it work with everything else they’re doing," said Rinke.

Constellation Research analyst Mike Ni covered the Celosphere 2025 keynote live from Munich. He noted that Celonis was making the case that process intelligence should be the brain of enterprise AI. Ni added that Celonis touted an ecosystem that includes Wipro, Microsoft and now Databricks.

In many ways, Ni said Celonis is positioning itself as a "multi-dimensional Digital Twin of Operations" and the "architecture for contextual AI."

"While the hot term is not always understood think of it as a living business graph that feeds AI reasoners solving the very hard problem of context structuring," said Ni.

• Agentic AI without process optimization, orchestration will flop
• Time to Introduce Hi-Fi for Enterprise Processes

He added:

"The underlying message: stop treating AI as a science project. Make AI operational. AI suffers without context. Celonis wants to give it memory. Celosphere 2025 isn’t about process mining anymore, it’s about decision mining: finding, understanding executing where AI should act."

Here's a deeper dive on the Celonis news.

Celonis added to its Process Intelligence Platform and built out its operational digital twin features. The company said Celonis Data Core is generally available with the ability to integrate with Databricks and Microsoft data lakes.

The company said that the Process Intelligence Graph includes the ability to connect desktop actions to business processes with new task mining capabilities and AI-driven task discovery. Unstructured data types are also integrated.

Celonis also added enterprise architecture blueprints that give a live view of operations. The company also added more than 60 pre-built objects and events including assistants for data extraction and data modeling.

Other additions include:

• New object-centric process mining (OCPM) capabilities to identify issues at process intersection points.
• An orchestration engine that now coordinates AI agents for end-to-end processes.
• Process Intelligence MCP Server.

As for the Databricks partnership, Celonis will leverage Databricks Delta Sharing for bi-directional integration. The integration means that joint customers won't need to move or copy data between platforms.

With the Databricks integration, Celonis can read live Databricks data and enrich it with business context and its Celonis Process Intelligence Graph to create digital twins. Process Intelligence from Celonis can then be fed back to Agent Bricks.

For Celonis to win over enterprise, it'll have to prove out its value in the data to decisions chain. Mercedes-Benz outlined how it uses Celonis for order-to-deliver, aftersales and quality management. Mercedes has integrated process intelligence with its AI and operations workflows.

Vinmar created a digital replica to automate order-to-cash, find distressed orders and remove friction from handoffs.

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

Clorox still has an ERP implementation hangover as the company reported a 19% decline in sales "primarily driven by lower shipments related to the ERP transition."

The company reported fiscal first quarter earnings of 65 cents a share on revenue of $1.43 billion. Adjusted earnings were 85 cents a share, down by 54% from a year ago.

Clorox had been on an SAP ERP system that was more than two decades old. It set out to upgrade SAP in 2021 and the final tab will range from $560 million to $580 million. As previously reported, Clorox wrapped up the ERP upgrade and was poised for better margins ahead.

However, Clorox executives said the company shipped more inventory for a buffer as it transitioned to the new ERP system. When retailers ran out of stock, Clorox ran into procurement issues.

• Time to Introduce Hi-Fi for Enterprise Processes

Here's what happened via CEO Linda Rendle and CFO Luc Bellet in prepared remarks.

• "At the end of last fiscal year, we shipped roughly two weeks of inventory ahead of consumption as retailers built stock in preparation for this transition. As those inventories were drawn down this quarter, we expected net sales to decline by approximately 17% to 21%. While the ERP systems cutover proceeded smoothly, we encountered some challenges in order fulfillment that led to temporary out-of-stocks."
• "Based on early estimates, we projected and communicated in early September that our first-quarter net sales were likely to come in at the low end of our guidance range. Ultimately, this quarter’s results exceeded these expectations for two key reasons: first, the impact of fulfillment disruptions was less significant than anticipated due to stronger-than-expected recovery in September; and second, we shipped ahead of consumption for some second-quarter merchandising events."

Clorox said it didn't help that the economy and consumers are under pressure. Clorox said consumers are showing "value-seeking behaviors across all income segments."

Now Clorox is focusing on regaining share from the temporary out of stocks. Executives also noted that the issues have been addressed and fulfillment processes have stabilized. Clorox concluded:

"Our transformation and ERP implementation strengthens our digital backbone and positions us to unlock meaningful operational efficiencies, margin expansion and superior value for our consumers. In an environment where consumer dynamics are changing rapidly, our new tools are allowing us to reach them in new and innovative ways, improving the returns on each dollar invested. With each wave of implementation, we’re gaining sharper insights and deeper operational visibility — enabling faster, smarter, and better execution."

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

Palantir continued to land commercial accounts as its third quarter results handily topped expectations. The company’s US commercial revenue was up 121% from a year ago.

The company reported third quarter earnings of $476 million, or 18 cents a share. Non-GAAP earnings were 21 cents a share on revenue of $1.18 billion, up 63% from a year ago.

Wall Street was expecting Palantir to report earnings of 11 cents a share (17 cents a share non-GAAP) on revenue of $1.09 billion.

During the quarter, Palantir announced partnerships with Hadean, Lear, Lumen Technologies and SOMPO. Palantir has increasingly been competing with more traditional enterprise software vendors and winning accounts via its data ontology and ability to deploy AI.

• Snowflake, Palantir forge data integration partnership
• Palantir's software revolution: Forget salespeople, let value do the talking

Based on the Rule of 40, Palantir blew that away with a score of 114%. CEO Alex Karp said the company’s US business growth was 77%. Most of Palantir’s revenue is focused on the US as well as western allies.

By the numbers:

• US revenue was $883 million in the third quarter.
• US commercial revenue was $397 million with US government revenue of $486 million, up 52% from a year ago.
• The company said it closed $2.76 billion of total contract value in the third quarter, up 151% from a year ago.
• Customer count was up 45% from a year ago.
• Palantir had $6.4 billion in cash and equivalents.
• In the third quarter, Palantir closed 204 deals worth at least $1 million, 91 worth at least $5 million and 53 worth at least $10 million.

As for the outlook, Palantir raised its outlook and projected 2025 revenue between $4.396 billion and $4.4 billion. Commercial revenue will top $1.43 billion. Fourth quarter revenue will be between $1.327 billion and $1.331 billion.

In a shareholder letter, CEO Alex Karp delivered his usual complement of strong quotes. He said:

• “This remains the beginning, the first moment of a first chapter.”
• “It is worth remembering that the business is now producing more profit in a single quarter than it did in revenue not long ago. This ascent has confounded most financial analysts and the chattering class, whose frames of reference did not quite anticipate a company of this size and scale growing at such a ferocious and unrelenting rate. Some of our detractors have been left in a kind of deranged and self-destructive befuddlement.”
• “Our partners in the United States—the earliest and most voracious adopters of the novel language models that are presently reordering human life and of the Ontology that allows them to effectively operate—understand how significantly the terrain beneath us all has shifted.”