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Gaurav Gupta reposted thisGaurav Gupta reposted thisNext month marks 10 years of ClickHouse as an open source project and we are thrilled to welcome our community at our annual user conference today in San Francisco. To everyone who contributed code, filed an issue, or ran ClickHouse in production from the beginning: thank you. Today, we’re proud to share that ClickHouse has over 4,000 customers, $250M in ARR, and is trusted by teams like Anthropic, OpenAI, Cursor, Lovable, Vercel and many more building the future of AI. In this post, I cover the milestone, what we’re shipping, and what comes next: https://lnkd.in/gra_Pjzu
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Gaurav Gupta reposted thisGaurav Gupta reposted this"There's only two ingredients you need: hard work and luck." Anthony Woods, co-founder of Grafana Labs, is putting this mindset into another mission. As the co-founder of the AOJ Woods Foundation, he has one clear intention: give away the vast majority of his wealth within his lifetime. Not someday. Now. The foundation will focus on three areas: neurodiversity, mental health, and youth disadvantage. At the center of it all — making the education system more inclusive for every child. "We realise that we have been very fortunate and that's something that we want to share with the rest of the world." Learn more: https://lnkd.in/gNV56M2t‘We’re not yacht people’: The couple giving away their ‘unicorn’ fortune‘We’re not yacht people’: The couple giving away their ‘unicorn’ fortune
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Gaurav Gupta reposted thisGaurav Gupta reposted thisThis video from Anthropic perfectly represents the new shape of the SOC, where agents accelerate detection and response workflows. Agents perform best when they can see internal company knowledge, multiple datasets, and broad security/IT tooling. That brings organizational context alongside the event logs, giving us the business-level justification for the signals we create in the SOC. As the interface to security workflows becomes prompt-based, there's real potential to scale who can collaborate on security and the volume of signals we monitor. Anthropic's security team recently shared a demo of what this looks like in practice. They use their system, CLUE, to orchestrate investigation and remediation, which gathers context from Panther, VirusTotal, and internal sources to assess risk and take next steps. Those findings close the loop, improving their overall security posture and remediating issues that surface along the way. The future is agentic! Check it out: https://lnkd.in/gGD9a_-4
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Gaurav Gupta reposted thisGaurav Gupta reposted this> What if Slack was rebuilt to be AI native in 2026? It'll feel like your workspace **woke up**. Started building this last year, and finally 30 days ago, switched over from Slack to PromptQL. Super excited share early launch of what it looks like and what it feels like!
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Gaurav Gupta reposted thisYesterday, 19 years to the exact date that I submitted my dissertation to complete the Ph.D. program at Stanford, I signed an agreement for my very first startup, SiftD.ai, to be acquired by Databricks. It's been an exciting roller coaster ride the last two years of working with Siegfried Puchbauer, Vishal Patel, and getting incredible support from many others, especially Gaurav Gupta and the Lightspeed team. Most importantly, it's been an incredible journey of learning and growth as we've explored the frontier of what agentic AI is capable of and how it best integrates with cybersecurity and other platform tools. Those learnings have convinced us that Databricks, with their long pedigree of combining data, compute, and machine learning, is in a unique position to harness the full potential of agentic AI, starting by reinventing the SIEM with Lakewatch. Our entire team is beyond excited to start our new journey with Databricks together.Gaurav Gupta reposted thisToday, we announced Lakewatch to disrupt the SIEM market. We also announced our acquisitions of Antimatter and SiftD.ai, bringing to Databricks some of the most impressive founders in cybersecurity: Andrew Krioukov, Michael Andersen, Steve Zhang, Vishal Patel, and Siegfried Puchbauer. Two career milestones: 1) First time announcing two deals in one release. 2) My 19th and 20th acquisitions in Corp Dev. https://lnkd.in/gkuG3rjDDatabricks Announces Lakewatch: New Open, Agentic SIEMDatabricks Announces Lakewatch: New Open, Agentic SIEM
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Gaurav Gupta reposted thisGaurav Gupta reposted thisHot take: your data strategy is more likely to derail your AI initiative than your model choice is 💀 Everyone's debating which LLM to use. Almost nobody is asking whether their data platform can actually serve it. In my latest post, I cover three converging shifts: real-time analytics, data warehousing, and observability — and why the architectural demands of AI (high concurrency, low latency, full-fidelity data) don't match what incumbent platforms were designed for. https://lnkd.in/gtmK3EGj
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Gaurav Gupta reposted thisGaurav Gupta reposted thisI gave a talk at AWS re:Invent on why enterprise AI keeps failing. Not because the technology isn't ready, but because we're building it wrong. Here's what I mean. Every chat-with-data product can technically work today. You can connect an LLM to your database, ask questions, get answers. The capability exists. But when a business user asks a loaded question with real impact, they know for a fact they can't trust the output. Even a human would struggle with that question, but at least the human signals uncertainty. AI just delivers a confident answer. This is the "confidently wrong" problem, and it's the real barrier. Not lack of capability. The issue is that AI never admits when it doesn't know something. And here's why that matters: you can only teach something when it says it doesn't know. Think about the humans you trust in business. They're not necessarily the smartest people in the room. What makes them valuable is their ability to pick up context, learn from failures, and signal when they're uncertain. That uncertainty is what lets you teach them. AI doesn't do this. So even when your AI is 90% accurate, you can't tell which answers fall in that problematic 10%. This forces verification on every output. Your team forensically checks results because one wrong answer costs more than ten correct ones. That verification tax destroys ROI. And you can't fix it through feedback because AI never signals that it needs help. The learning loop is broken before it starts. The solution isn't complicated. Build systems that explicitly signal confidence. Show users what the AI knows versus what it's assuming. When it encounters something unfamiliar, flag it. Let domain experts step in naturally. Capture that knowledge. That conversation between user and expert becomes the seed for improvement. The system learns through actual work instead of requiring some separate training process. This is what allows systems to scale beyond the 20-25 table limits you see elsewhere. When AI can admit uncertainty and learn from feedback, the scale problem becomes solvable. Without that loop, more scale just means more confident wrongness. The market thinks enterprise AI is failing because models aren't capable enough. That's wrong. Enterprise AI is failing because systems haven't been designed to communicate limits and learn from feedback. The fix isn't bigger models. It's humbler ones that know when to ask for help. --> Full talk linked in comments.
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Gaurav Gupta reposted thisGaurav Gupta reposted thisThis morning, Business Insider featured PromptQL among four AI startups reimagining how enterprises get insights and make decisions - a validation of a bet we made a year ago! The article frames this wave as “AI consulting startups.” The way I see it, it’s the next evolution of consulting - when the expertise, reasoning, and depth of a consulting team become instantly available to everyone through AI. And that’s only possible when accuracy scales. BI quoted what I told them was our “killer feature”: 🟢 “AI accuracy at scale without requiring messy data to be prepped or moved elsewhere.” No six-month data migration projects. No cleanup tax. Just AI that works on your data as it exists today, and learns your business on-the-go to tell you when it’s unsure. Lightspeed’s Gaurav Gupta says it best: ⏩ “We believe 95% of AI companies will fail, and history will show that hallucinations were a major reason why.” Unfortunately that’s not a prediction. That’s already happening. Read the full article in the comments.
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Gaurav Gupta liked thisGaurav Gupta liked thisNext month marks 10 years of ClickHouse as an open source project and we are thrilled to welcome our community at our annual user conference today in San Francisco. To everyone who contributed code, filed an issue, or ran ClickHouse in production from the beginning: thank you. Today, we’re proud to share that ClickHouse has over 4,000 customers, $250M in ARR, and is trusted by teams like Anthropic, OpenAI, Cursor, Lovable, Vercel and many more building the future of AI. In this post, I cover the milestone, what we’re shipping, and what comes next: https://lnkd.in/gra_Pjzu
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Gaurav Gupta liked thisGaurav Gupta liked thisAfter five years at J.Jill that went by faster than I can believe, I am embarking on a new chapter. And this chapter starts with a luxury that I feel incredibly fortunate to have: a summer completely off with my kids (and Dan O'Malley, though he’ll still be working!). My time at J.Jill was made truly remarkable by the team I had the privilege to lead and collaborate with. They are a rare mix: analytical, deeply creative, customer-obsessed, and entirely low-ego. Together, we tackled a massive amount of evolution—modernizing the brand, expanding our reach through inclusive sizing, hyper-growing channels like SMS, evolving our technology platforms, leaning into AI, and introducing new mediums like broadcast. I am incredibly proud of what we built, but even prouder of how we worked together every day. J.Jill is the first company I’ve worked for where I am actually the target customer. Because of that, I’m excited to transition into a new role: an enthusiastic loyal customer, benefitting from the continued evolution of the product, brand, and experience. My immediate focus is mastering the art of the summer break. Please send beach read and day trip recommendations my way, and let me know if you’d like to grab lunch or a drink. I am officially available!
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Gaurav Gupta liked thisGaurav Gupta liked this"There's only two ingredients you need: hard work and luck." Anthony Woods, co-founder of Grafana Labs, is putting this mindset into another mission. As the co-founder of the AOJ Woods Foundation, he has one clear intention: give away the vast majority of his wealth within his lifetime. Not someday. Now. The foundation will focus on three areas: neurodiversity, mental health, and youth disadvantage. At the center of it all — making the education system more inclusive for every child. "We realise that we have been very fortunate and that's something that we want to share with the rest of the world." Learn more: https://lnkd.in/gNV56M2t‘We’re not yacht people’: The couple giving away their ‘unicorn’ fortune‘We’re not yacht people’: The couple giving away their ‘unicorn’ fortune
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Gaurav Gupta liked thisGaurav Gupta liked thisA joy to meet Satya Nadella at a time when we are seeing surging demand for ClickHouse on Microsoft Azure. And always fun catching up with Bipul Sinha.
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Gaurav Gupta liked thisGaurav Gupta liked thisThis video from Anthropic perfectly represents the new shape of the SOC, where agents accelerate detection and response workflows. Agents perform best when they can see internal company knowledge, multiple datasets, and broad security/IT tooling. That brings organizational context alongside the event logs, giving us the business-level justification for the signals we create in the SOC. As the interface to security workflows becomes prompt-based, there's real potential to scale who can collaborate on security and the volume of signals we monitor. Anthropic's security team recently shared a demo of what this looks like in practice. They use their system, CLUE, to orchestrate investigation and remediation, which gathers context from Panther, VirusTotal, and internal sources to assess risk and take next steps. Those findings close the loop, improving their overall security posture and remediating issues that surface along the way. The future is agentic! Check it out: https://lnkd.in/gGD9a_-4
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Patents
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Data Volume Management
Issued US 8,682,930
Embodiments are directed towards a system and method for a cloud-based front end that may abstract and enable access to the underlying cloud-hosted elements and objects that may be part of a multi-tenant application, such as a search application. Search objects may be employed to access indexed objects. An amount of indexed data accessible to a user may be based on an index storage limit selected by the user, such that data that exceeds the index storage limit may continue to be indexed. Also…
Embodiments are directed towards a system and method for a cloud-based front end that may abstract and enable access to the underlying cloud-hosted elements and objects that may be part of a multi-tenant application, such as a search application. Search objects may be employed to access indexed objects. An amount of indexed data accessible to a user may be based on an index storage limit selected by the user, such that data that exceeds the index storage limit may continue to be indexed. Also, one or more projects can be elastically scaled for a user to provide resources that may meet the specific needs of each project.
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Startup Researcher Europe
5K followers
Dust raised a $40 million Series B led by Abstract and Sequoia, with Snowflake Ventures and Datadog participating. The company provides an operating system for businesses to deploy and manage collaborative AI agents that work alongside teams to compound organizational intelligence. Founded by Gabriel Hubert and Stanislas Polu, Dust's platform enables a "multiplayer AI" system where humans and agents collaborate in shared workspaces. The goal is to move beyond single-user AI to unlock compounding productivity gains across an organization. More at: https://lnkd.in/dPz-gREb #AI #EnterpriseAI #Funding
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Hasmukh Ranjan
AMD • 8K followers
Great insights from our AMD IT team in Part 2 of this AMD IT series. As we accelerate AI across the enterprise, I’m reminded that scalable innovation doesn’t start with models — it starts with strong, well-governed data foundations that we build with intention and discipline.
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1 Comment -
Gaurav Bhogale
Mantis Venture Capital • 11K followers
This breakdown nails it. Too often, teams start a BYOC effort thinking it’s just an “infra wrapper,” and quickly find themselves knee-deep in platform engineering. Supporting multi-tenant deployments across cloud environments, complete with secure auth, secrets management, upgrades, and Day-2 ops; while still offering a polished install experience isn't trivial. The real cost is in distraction. Every hour your DevOps team spends patching Helm charts, managing install scripts, or untangling client VPC issues is an hour they’re not building your core product. Platforms like Nuon led Jon Morehouse help teams ship BYOC faster, with fewer landmines and a much cleaner ROI. Appreciate how clearly you laid this out Mark Milligan. If you’re an infra team wrestling with BYOC, or just starting to think about it, feel free to reach out. Always happy to jam!
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Idan Zachar
Awz • 7K followers
Google just launched Gemini Enterprise, and it quietly marks a major turning point. Gemini Enterprise isn’t just another model release. It’s about embedding intelligence inside the enterprise where AI doesn’t assist from the sidelines but starts to act, connecting to data, reasoning across systems, and executing real tasks. Strategically, this is smart positioning. While Microsoft and OpenAI compete on models and features, Google is playing the long game, building the platform layer where enterprise AI actually lives. It’s not about winning the model race, it’s about defining the infrastructure of intelligence. For executives, the real question isn’t “which AI should we use?” it's: “how do we redesign our organization so AI can work within it and create value?” That’s the shift. When AI becomes part of how decisions are made, how workflows run, and how value is created, that’s when transformation stops being a buzzword and becomes reality. #AI #Leadership #Strategy #DigitalTransformation #ArtificialIntelligence #EnterpriseAI #Innovation #CLevelLeadership #BusinessTransformation
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KonnectHouse - Procurement insights
6K followers
🚀 Levelpath Raises $55M Series B Led by Battery Ventures to Advance AI-Native Procurement Platform Levelpath has announced $55+ million in Series B funding led by Battery Ventures, bringing total funding to $100 million to accelerate its mission to reinvent enterprise procurement through autonomous AI agents and its proprietary Hyperbridge reasoning engine. ✨ The round includes participation from Redpoint Ventures, Benchmark , 01 Advisors, NewView Capital, and WiL (World Innovation Lab). Battery Ventures General Partner Neeraj Agrawal, who previously led the firm's investment in Coupa Software (acquired for ~$8 billion in 2023), joins Levelpath's board and has made multiple appearances on the Forbes Midas List. "Levelpath represents the future of enterprise procurement: intelligent, automated, and strategically aligned with business objectives," said Agrawal. "The team has built remarkable technology that delivers demonstrable value to some of the world's largest companies." Alex Yakubovich, Co-founder and CEO of Levelpath, adds: "Procurement touches every part of a business, yet it's been held back by tools that fight against you instead of working with you. We didn't retrofit old systems with AI. We reimagined what procurement could be when intelligence is built into every interaction." Stan Garber, Co-founder and President, comments: "We're not just building procurement tools, we're building the intelligent infrastructure that turns procurement into a competitive edge that will radically accelerate productivity at scale." The funding will accelerate product development of AI Agents that autonomously handle sourcing events, supplier onboarding, and risk assessments while scaling go-to-market efforts and ecosystem partnerships. Read the full announcement here: https://lnkd.in/e3ATgcNw #AINativeProcurement #ProcurementAI #SeriesBFunding #AutonomousAI #ProcurementTransformation
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Tech Lens Media
688 followers
Enterprise software only creates value when it's implemented correctly. Yet implementation has run on the same patchwork of meetings, spreadsheets, and tribal knowledge for decades. Requirements scatter. Context gets lost. Margin erodes. Auctor just raised $20M led by Sequoia Capital with Y Combinator, M12, Microsoft's Venture Fund, Workday Ventures, HubSpot Ventures, and OneStream to fix that. One traceable system for every implementation. Execution-ready artefacts. Repeatable best practices. Teams are seeing up to 80% efficiency gains. Weeks of work compressed into hours. Hundreds of billions spent annually on enterprise implementation. Nobody built a category for it. Until now. Is software implementation the most underleveraged category in enterprise tech right now? Follow Tech Lens Media for more high-signal takes on enterprise AI and SaaS infrastructure. #TechLensMedia #EnterpriseAI #SaaS #SeriesA #Sequoia #SoftwareImplementation #AIStartup
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1 Comment -
TrueFoundry
26K followers
We just published a technical case study on how Aviva Crédito operationalized multi-cloud LLMs (Azure + GCP) with TrueFoundry AI Gateway. A few engineering takeaways you might find useful: - One stable gateway interface across providers/models (less SDK churn as models change) - Centralized tracing for latency/failures + cost attribution by service/team - Latency-aware fallback routing to keep p99 spikes from becoming incidents - Semantic caching at gateway level to avoid unnecessary api calls Case study: https://lnkd.in/gQ-GmJtM Thanks Matthieu Perrinel Enrique Maffezzini for building systems using TrueFoundry. We are happy to take this partnership forward 🚀
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Creative Spark Solutions
7 followers
I truly believe the evolution of the AIOS will come from freedom, not lock-in. The winning systems will not force people into one model, one vendor, or one way of working. They will be built on an agnostic orchestration layer that can coordinate across LLMs, agents, tools, workflows, and business systems — while supporting universal knowledge transfer, where context, memory, approvals, and outcomes can move safely between environments. That is where AI becomes more than another app. It becomes an operating experience that adapts with the user, protects the business, and compounds knowledge over time. The future is bright.
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IRIS - Canon Group
16K followers
📈 Scaling document intelligence is a performance problem: throughput, latency, and consistency at volume. IRIS SDKs are designed to embed into partner products and handle large page flows with predictable behavior-so teams can integrate once and scale across customers without rebuilding the core engine. ✅ Explore the IRIS SDK architecture: https://lnkd.in/eFyHC7Xh #IRISDataIntelligence #SDK #APIs #EmbeddedTech #Scalability
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Kit Yu
33K followers
Potential 2026 positives: 1) Improved capacity position drives AWS acceleration; 2) improving AI positioning due to mgmt. changes and 1P tech improvements; 3) incremental Retail margin expansion drives profit growth above peers; 4) Multiple positive Retail segment drivers including grocery, agentic AI, & Prime offering/fee increases; and 5) attractive valuation (vs history) leaves room for multiple expansion.
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Vedika Jain
Weekend Fund • 8K followers
𝗛𝗲𝗿𝗲'𝘀 𝘄𝗵𝘆 𝗪𝗲𝗲𝗸𝗲𝗻𝗱 𝗙𝘂𝗻𝗱 𝗶𝗻𝘃𝗲𝘀𝘁𝗲𝗱 𝗶𝗻 𝗗𝗲𝗮𝗹𝗼𝗽𝘀 𝗣𝗿𝗶𝗰𝗶𝗻𝗴 𝗶𝘀 𝗴𝗲𝘁𝘁𝗶𝗻𝗴 𝗺𝗲𝘀𝘀𝘆. Flat-rate and seat-based models are giving way to usage-based, hybrid, and outcome-driven models...and companies are iterating weekly. And yet…most deals are still priced in spreadsheets, Slack threads, and CPQs built for a world where pricing changed once a year. That’s why we invested in DealOps. Their platform cuts quoting time from ~30 minutes to 2–3 minutes while increasing ACVs and margins. It can: - Map use cases to SKUs (critical as platform companies explode in SKU count) - Automate forecasting (needed with usage-based pricing) - Generate polished proposals in one click 𝗙𝗼𝘂𝗻𝗱𝗲𝗿 𝘃𝗮𝗻𝘁𝗮𝗴𝗲 𝗽𝗼𝗶𝗻𝘁 Spyri priced thousands of deals at Stripe as part of the finance team, saw the limits of current tools firsthand, and has lived this problem end-to-end. 𝗦𝘁𝗿𝗼𝗻𝗴 𝗺𝗮𝗿𝗸𝗲𝘁 𝗽𝘂𝗹𝗹 They're off to a strong start. Teams like Plaid, Harvey, and Airwallex use DealOps to scale new pricing models, guide reps in real time, and drive pricing discipline without slowing deals. The results: 10× faster quoting, 30% lifts in average contract size, millions in incremental revenue. They’ve already processed over $1 billion in revenue, and are just getting started. 𝗧𝗵𝗲𝗶𝗿 𝘁𝗶𝗺𝗶𝗻𝗴 𝗶𝘀 𝗿𝗶𝗴𝗵𝘁 The entire AI supply chain, from GPUs to infrastructure, is variable COGS. Pricing agility is no longer a “nice to have”; it’s a must-have. We’re thrilled to back Spyri and the team alongside Pear VC, General Catalyst, and others as they build the pricing system of record for modern sales teams.
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Wiz
410K followers
Say hello to WizOS: Now in Public Preview! 💥 What is WizOS? Minimal, secured container images built and maintained by Wiz, with near-zero CVEs. But here's the real shift: This isn't just an image catalog >> It's an extension of the Wiz platform that: 1) Surfaces visibility into every image across your environment 2) Prioritizes image swaps based on real risk 3) Enables one-click image swaps right in developer workflows With WizOS, the secure choice becomes the easy choice, reducing vulnerabilities at scale by acting on the base image, not chasing CVEs one by one. Learn more: https://lnkd.in/ec-VV967
831
14 Comments -
ScyllaDB
29K followers
ScyllaDB was created to go beyond Cassandra’s suboptimal resource utilization. By utilizing a low-level engineering approach, Dor Laor and Avi Kivity believed they could squeeze considerably more power from the underlying infrastructure. Felipe Cardeneti Mendes looks at the capabilities that set us apart from Cassandra > https://lnkd.in/ej8nAzpb #ScyllaDB
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Yanai Oron
17K followers
- Viral milestone: 1,000,000 views - Michael Bargury and Zenity’s research crew drew major attention at Black Hat - They showed practical attack paths on ChatGPT, Cursor, Microsoft Copilot Studio, and Salesforce - Next step for teams using AI agents: assess and harden
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2 Comments -
JFrog
95K followers
Writing code with AI is fast, but releasing it is not - Until now... Introducing JFrog Fly, the world's first agentic artifact repository. ✈️ It gives #AI agents the context they need (commits, PRs, issues) to manage your releases. This is agentic release management for AI-native teams. Learn more: https://bit.ly/4qLsJJJ #DevOps #AINative #AgenticAI #ReleaseAutomation
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Hilary Gosher
Insight Partners • 5K followers
Using real world examples from Optimizely , Hinge Health, Aptean , Diligent , Copado , Brinqa , CentralReach and Fin, this shows how companies have pivoted AI product strategy and operations to embrace #AI transformation. Companies need to adapt or risk their future.
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Norman Volsky🎙️ 🏥 📉
Bending The Trend • 25K followers
So what is Scala? Hear Ardie Sameti co-founder and CEO explain how Scala is changing the game by helping to unify fragmented data and surface up what actually matters. If your head is dizzy from complex data, and you need to clarify those signals, you should learn more! "The gold is the data" Hear Ardie walk us through his incredible time at Accolade, the impact of core values and mentors, data and operational intelligence, and more! Theres a lot to learn this week on the Digital Health Heavyweights Podcast, check it out here: https://lnkd.in/gHcwrfyD
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Tomasz Tunguz
Theory Ventures • 406K followers
Why was the Fivetran-dbt merger all but inevitable? Fivetran & dbt Labs announced their merger yesterday. The all-stock deal combines two companies into an entity approaching $600 million in ARR. The beauty of the modern data stack was the explosion in choice. As the cloud exploded onto the scene, the legacy data warehouse was replaced by a collection of fast-moving platforms. In that era, specialization won. The pendulum is now swinging back towards consolidation. Why? The answer lies in compute economics & revenue scale asymmetry. The table below shows why. There are three different categories of software within this subset of the ecosystem: 1. Ingestion takes data from software & moves it into a cloud data warehouse. Snowflake acquired Datavolo, which commercializes the open source product Apache NiFi, calling it Openflow. Databricks acquired Arcion for ingestion through change data capture, calling it LakeFlow Connect. Fivetran focuses exclusively on this layer. 2. Transformation means reformatting the data within the cloud data warehouse. Snowflake launched native dbt Projects on Snowflake. Databricks offers Delta Live Tables, native SQL, & Python, plus supports hosted dbt through Databricks Workflows. dbt Core/Cloud is the leading independent transformation tool. 3. Compute revenue is generated when we ask questions of our data. Snowflake remains one of the leaders in structured data analysis with their cloud data warehouse. Databricks’ compute is their own as well. Here’s the asymmetry in one number. Compute represents 72% of the overall market ($7.6B of $10.6B). As a result of their massive operations, Snowflake & Databricks exert significant gravity within the ecosystem. They have expanded beyond the compute market to impose their presence & capture marginal revenue within customers, pressuring the competitive ecosystem. That’s not to say these components are independent. George Fraser analyzed Snowflake workloads in September 2024, finding transformation represents 40-45% of total Snowflake compute, which means even at smaller scales, startups can have significant impact on these behemoth businesses. The Fivetran-dbt merger is an inevitable evolution of a maturing market. Two unicorns must partner to compete against two decacorns. They solve two of the three customer problems. But not yet compute. One could surmise this consolidation signals the end of the modern data stack. I view it differently. The MDS has succeeded beyond our expectations. The stakes are higher now. Broad platforms, fast growth, & AI-native architectures define the next phase. Expect more consolidation. Category revenue estimates based on public disclosures & company filings. Ingestion: Informatica ($1.64B FY2024), Fivetran ($300M est.), Talend ($350M), others ($200M est.). Transformation: dbt Labs ($300M est.), others ($200M est.). Compute: Snowflake ($3.6B FY2025), Databricks ($4.0B ARR Aug 2025).
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9 Comments -
Carlotta "Lotti" Siniscalco
Emergence Capital • 11K followers
The best AI apps today are being built like infrastructure companies. Great breakdown from the awesome 💡 Yazan "Yaz" El-Baba on why technical depth, rapid iteration, and margin-aware architectures are becoming table stakes for AI startups. Definitely worth a read: https://lnkd.in/gMVFFXgH
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