fulfillmenttools

Our team just got stronger. ☁️💪 Meet Joshua L. - Senior Cloud Engineer at fulfillmenttools as of July! Joshua is joining our Product & Technology department and will be a key part of building and scaling the cloud infrastructure that powers our platform. Welcome aboard, Joshua! We're really glad you're here! 🚀 Give Joshua a warm welcome in the comments! ⬇️

We're proud to announce that Christ Juweliere und Uhrmacher seit 1863 GmbH has chosen fulfillmenttools as Agentic OMS 🙌 Read Linda Kuhr's post below and our latest press release for more information 👉 https://lnkd.in/ejuXQbNs

Most conversations about AI agents focus on one question: 👉 Can they act autonomously? The more important question is: 👉 What should they be allowed to act on? In the latest article of the Agentic Order Management series, we explore why full autonomy is not the goal. It's scoped autonomy. Swipe ➡️ to find out what this means in practice.

🌸 Every bouquet is a promise. Keeping it at scale is the hard part. At K5 - Future Retail Conference, our Head of Customer Success Mark Byerly hit the stage with Lydia Oertel from BLUME2000 SE to unpack how they run order management for a business where a wilted delivery is a broken promise, not just a late package. In this masterclass, Lydia and Mark talk through: 🌱 The operational reality behind promising and fulfilling flower orders 🌱 How BLUME2000 built reliability into a notoriously perishable, time-critical supply chain 🌱 What it takes to make "in-full, on-time" work when the product itself has a shelf life Watch the full masterclass: https://okt.to/AJMZN2

Ask a vendor if their AI agent is autonomous. They'll say yes. 🤖 Read the fine print: it surfaces an insight, drafts a recommendation. A human clicks approve. Fine product. Wrong label. And that's exactly where buyers start losing trust. Full autonomy is also the wrong goal for an OMS. These are decisions with real consequences: sourcing, rebooking, compensating customers. What works is scoped autonomy, in three modes: 👉 Notify — the agent acts, then tells you 👉 Approve — the agent proposes, ranks trade-offs, waits 👉 Co-decide — the agent brings the analysis, the human calls it And every action needs to be explainable, traceable, and reversible. "The AI did it" is not an answer for a customer, an auditor, or a board. Product Marketing Manager Daaron Eßers wrote about how this shapes our Order Monitoring Agent and Order Routing Agent 👇 https://okt.to/QDY9NZ

fulfillmenttools is now recognized as Leader in Picking and Top Rated in Order Management (Q3/26) on OMR Reviews — with a 4.8/5 average rating. 💪 No marketing spin, just real customers rating what actually happens on the warehouse floor and at the checkout: order routing, availability, and getting picks right. Thank you to everyone who took the time to leave a review. 🙌 Check out our profile here 👉 https://okt.to/s8nytk

Everyone's talking about AI in commerce. But who's taking care of the delivery promise? ✨ Last week, at MACHmittag AI BBQ by kernpunkt, Jan, Sebastian Schaum and Oytun made the case: without a strong OMS at the backbone, every AI commerce vision stays theoretical. Smart routing, real-time inventory, transparent order status — these are the foundations that AI agents actually depend on. Big thanks to our partner kernpunkt for the event & the delicious BBQ and to all attendees for the conversations. See you next time. 🙌

Top 3 at the Retail Innovation Award 2026 — and we are proud to take it. 🙌 fulfillmenttools was nominated as a finalist at the Retail Innovation Award by DHBW Heilbronn , alongside some of the most exciting companies in retail tech. Huge congratulations to Trigo on the well-deserved win, to the fellow finalist Sensei and to everyone in the room: the inspiring conversations, the ideas, the ambition. That's exactly the kind of energy that makes retail's future so exciting! See you at the next one. 🚀 #retailtech #omnichannel #fulfillmenttools #RetailInnovation

Stale inventory data is the quietest way to break an AI agent. The agent does everything right. It reads the data, it makes the call, it routes the order. But the store sold its last unit two minutes ago, and the system had not caught up yet. Technically correct decision. Operationally wrong outcome. A human might catch it with judgment. An agent operating across thousands of orders has only the data to rely on. That's the reason why real-time inventory is the foundation every AI agent depends on. Not frequently updated. Real-time. Changes visible across the whole network the moment they happen. Our latest article breaks down what real-time inventory actually means, why agents depend on it, and what it takes to get right at enterprise scale.