Christophe Borg

After working with dozens of large retailers, I've learned rip-and-replace strategies don't work for companies with complex existing systems and millions in sunk OMS-stack costs. It’s called OMS lock-in. —> The legacy OMS has become too fixed for business operations. Removing it would disrupt critical workflows across multiple departments plus require massive retraining. —> Sunk costs make replacement financially unrealistic. Enterprises have spent years customizing their OMS, building integrations, and training teams. Writing off these investments is often more expensive than augmentation. The solution? A dual-OMS order operations intervention – an augmented approach preserving investment while adding intuitive capabilities. These modern order operations platforms can handle the workflows that legacy systems struggle with – rapid channel expansion, real-time inventory sync and complex routing logic while leaving established processes intact. This approach lets enterprises get modern capabilities without the risk and disruption of full replacement. They can test new approaches on a subset of orders before broader rollouts. Examples of successful dual-OMS implementations:   • One $2B retailer uses their legacy OMS for established retail channels while routing all marketplace and social commerce orders through a modern order operations platform. They expanded to new channels without disrupting existing operations.   • Another enterprise manufacturer kept their ERP-integrated OMS for B2B orders while implementing order operations for their growing DTC business. They got the speed and flexibility needed for consumer markets without changing established B2B workflows. Ready to evaluate your augmentation vs. replacement decision? Review these questions:   • Which order types create the most operational friction with your current system?   • What % of your business could benefit from modern capabilities?   • How much disruption would full replacement create across departments?   • Can you achieve strategic goals through selective augmentation? The most successful enterprise retailers think architecturally, not monolithically. They build hybrid systems that leverage existing investments while adding modern capabilities where they create the most value. Learn how to break the OMS lock-in chains without disrupting operations or starting from scratch—link in comments.

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Trust is a core value at Snowflake. It goes beyond governance, security, and precision. It’s about how we operate and how we partner with our customers. We believe in being a responsible steward of every dollar our customers invest in Snowflake and their data. That’s why it’s great to see customers like IGS Energy lowering the cost of training AI/ML forecasting models by 75% by moving from competitive providers to Snowflake. That’s real impact, enabling them to do more with AI on Snowflake. https://lnkd.in/eNQdDw5u

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🚀 Really excited for this launch: Vantage is launching Audit Logs for tracking platform changes. You can now see a paper trail of changes made on the platform (i.e. virtual tag updates, cost report creations, etc.), who made those changes and when they occurred. Our customers are increasingly inviting more and more of their team-members to Vantage accounts. It's becoming common that organizations have hundreds or even thousands of employees in a single Vantage account, each set up with their own reports, dashboards and budgets. With such significant adoption comes lots of changes and, over time, it can be tricky to see what changes in the platform are occurring, who made them and how. As a result, we've launched a devoted Audit Log section under the Settings portion of the Vantage console. You can see a running list of changes occurring within your Vantage account, the date they occurred, what object it was performed on (i.e. Cost Reports, Virtual Tags, etc) and who made the change. You can also filter on all of these dimensions as well to find exactly what you're looking for. I love how quickly we can receive customer feedback from #FinOps practitioners and build a best in class, modern and intuitive product experience. The team is really rolling. This feature is live to all of our customers beginning today and you can read the full blog post with all the details below.

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So excited to announce this morning that we officially launched Logicbroker Data Pipeline 🚀 - this is going to let our customers sync their data to any cloud storage or data warehouse of choice with no developers, no code, in mere minutes with just a few clicks 🤯 Not even kidding... this used to take customers months of dev effort and $100,000s of dollars of investment to stand up something comparable that wasn't even as effective - game changer 🎮 Customers will now be able to create a single source of truth for data intelligence, so they can make smarter decisions and answer questions like which suppliers have the fastest fulfillment times across all channels and what are the real shipping costs per channel for a particular region. Right from the get go, we will support connectivity to Databricks, Snowflake, Microsoft Azure Blob Storage, Google Cloud Storage, Amazon Web Services (AWS) S3 or Redshift ☁️

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Today Entrata announced a $200M investment from Blackstone, fueling our continued investment in the future of multifamily technology. We’re building products that simplify operations, elevate the resident experience, and unlock new value for the industry. This investment allows us to go faster and further—especially with solutions like ELI+ and Homebody leading the way. I am so excited for what’s next for our team and our products! For more on today's announcement, head to https://lnkd.in/gWtjbpte #PropTech #Entrata #Blackstone #MultifamilyInnovation

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💡 The enterprise GenAI hype is loud... but real impact remains rare. A latest AI in the Enterprise 2025 report debunks some persistent myths and brings much-needed clarity on what’s really happening in the field: 1️⃣ Mass layoffs? Limited and highly sector-specific. GenAI’s impact is mostly focused on content creation, support, and analytics. No executive consensus on long-term hiring. 2️⃣ Enterprise adoption? Lots of experimentation, but only 5% of projects make it to production. Leaders want ROI... but struggle to scale. 3️⃣ Biggest blocker? Not the model quality, but poor integration into existing workflows. Most tools don’t adapt to how people actually work. 4️⃣ Custom-built tools? Extremely hard to scale. Without deep workflow integration and continuous learning, internal tools often fail and users switch back to general-purpose tools. 5️⃣ Core business transformation? Not yet. In 7 of 9 sectors, GenAI hasn’t meaningfully reshaped operations. 🧭 What should companies do now? ✅ Focus on a few high-value, operational use cases 🧰 Leverage general-purpose tools for productivity, but continue to protect sensitive data 📈 Scale with workflow-native, learning-enabled tools not broad demos or flashy features 📊 And don’t overlook less flashy investments: predictive AI, business intelligence, and solid data infrastructure often deliver more immediate and reliable value We’ve seen this cycle before with big data 10 years ago. Let’s not fall into the same trap with GenAI and move to another AI Winter. 💬 How are you moving from GenAI experiments to real impact in your organization?

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Everyone keeps saying “enterprise agents are coming.” They’re right; but yet this still misses the point. The bottleneck isn’t model intelligence. It’s trust. We already have capable reasoning models. What enterprises don’t yet have are engineering harnesses to take that autonomy and deploy agents into something enterprises can safely deploy, monitor, and fully utilize to do real work. Evals, Observability, Authorization, many other primitives. Building solid harnesses that put to rest these thorny little enterprise-ey issues represents the 'final unlock' — and ultimately will lead to the trillion-dollar opportunity in AI being realized. In this post with my Chemistry colleague Ivory Tang, we argue that agents won’t win by being smarter. They’ll win by being trusted — and that trust is now an engineering problem, not a research one. The winners won’t be the ones that build the most agents; instead, they’ll own the surface where agents earn trust in production. Link to post in comments. Send us thoughts, reactions, ideas, and founders!

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Just read a CIO.com piece on what’s “in” and “out” for digital transformation in 2026, and one callout jumped off the page: AI-powered browsers. These tools don’t just “browse.” They can interact with logged-in apps (email, CRM, repos), remember context, and help people draft, summarize, and automate work inside the browser. That also means sensitive information can get copied, pasted, and sent in ways many traditional security tools never see. That’s why I appreciated the perspective from Rohan Sathe (Co-Founder & CEO at Nightfall AI) in the article. What I like about this: it names what a lot of teams are missing. Traditional protections weren’t built to see prompts, clipboard actions, or browser-level workflows. This is also where Nightfall AI comes in. The approach is built for how work happens today: seeing and protecting sensitive data while people are using web apps, not just after something is saved or emailed. It can help identify things like customer data, financial details, and other sensitive info as it’s being entered or shared, so teams can use modern tools without turning every prompt into a data leak. Worth reading if AI is on your roadmap, because “we’ll secure it later” usually turns into “we didn’t see it happening.” Read the CIO.com article: https://lnkd.in/gc8Vi_8N Nightfall’s write-up: https://lnkd.in/g-2Yi8ky #JasonMakevich #Cybersecurity #DataProtection #AIGovernance #AI #RiskManagement #DigitalTrust #Privacy #SecurityLeadership #Nightfall

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I had the chance to sit down with Anthony Bonaduce from Cosmos Data Technologies, a company doing something pretty unique in the Business Central space. Cosmos was built from the ground up as a cloud-native reporting and analytics platform, the only one that’s purpose-built specifically for Business Central Cloud. Anthony walks us through how they spotted a gap in the market, what it took to fill it, and how their team of longtime industry pros is scaling fast. We also talked about: • The company’s rapid growth (adding 25+ new customers a month) • Why 130+ Microsoft Partners have joined the program • What to expect from Cosmos' major upcoming release on August 25 • How they’re helping Partners deliver reporting that resonates with end users If you're working with Business Central or building in the Microsoft ecosystem, it's worth a listen. -- #PartnerTalks #BusinessCentral #Dynamics365 #Reporting #MicrosoftPartners #Cosmos #CloudERP #RickMcCutcheon

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It's time to retire the stacked layers graphic. In practice, separate layers of data is nice to look at but it doesn't answer questions. The way to get answers is to combine the data and query across it together. LeafLake allows you to get immediate answers to questions like "which variety had the highest yield last year, after controlling for soil type and fertilizer applications?" or "in which environmental conditions did this biological product perform best?". These work at the field level, and across millions of fields all with the same simple queries. Out of the box, LeafLake includes Weather, Imagery, Soil, Topography, Irrigation, and of course (if you have growers connected via Leaf), Management Data like Planted, Applied, Harvest, and Tillage. You can also load your own data to find even more relationships. No setup, maintenance, or data engineering. Focus on analysis and answers. Please reach out if you'd like to see a demo. https://lnkd.in/eecjzvYW

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Big week for the data community! dbt Labs and Fivetran are coming together to create something new: open data infrastructure. It’s a shared foundation for data movement, transformation, and activation—built to be open, reliable, and interoperable across every platform. This is the next chapter for analytics and AI, and we’re just getting started. See how we’re building the foundation for analytics, AI, and agents https://lnkd.in/eeHncGb6

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A.I. Clouds are not all the same. Justin Gage of Amplify Partners shares, in explicit detail, how Modal is just built different, and why it's a mistake to think of them as an "inference provider". https://lnkd.in/gmaYQZtT

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AI isn’t just for tech giants - even a local moving company is pulling off things that seemed barely possible. 3 Men Movers, a Houston-based moving firm, deployed AI cameras in their trucks to automatically detect distracted driving and alert drivers in real time. The result? In just the first 3 months, this AI reduced accidents by 4.5% by preventing 80% of distraction incidents. They’ve also plugged in an AI route optimizer to find the fastest paths for their 100-truck fleet. Ten years ago, you’d never expect a mid-sized mover to run an AI safety system usually seen in high-end trucking fleets. But here we are – affordable AI tools are helping even small businesses operate more safely and efficiently than ever. Congratulations to Jacky Fischer and the rest of the 3 Men Movers team for showing the way to lead with AI. https://lnkd.in/gx6_SqYk

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