Amazon releases new dataset for visual defect detection in retail

Amazon released Quick Suite—a single workspace that jams together AI-native BI, research agents, and workflow automation. Everything runs on natural language. No clicks, just prompts. The suite packs four pieces: Quick Index: a locked-down knowledge base for internal corporate brain dumps. Quick Research: scrapes across sources and returns straight-shooting answers. Quick Sight: BI you can talk to. Query dashboards like you're texting a data analyst. Quick Automate: builds (and babysits) workflows with human-in-the-loop triggers. https://lnkd.in/e-pF6Zgp --- More tech like this—join us 👉 https://faun.dev/join

Amazon's internal forecast suggests a $700 million financial gain from its AI shopping assistant Rufus in 2025, $1.2B by 2027. Amazon plans to fivefold the size of the AI model powering Rufus

When you order a book from Amazon using Amazon Prime, do you care about: A) Amazon’s algorithmic regionalised fulfillment nodes and their optimized last-mile distribution orchestration via adaptive geospatial carrier allocation. or: B) That the book will arrive before 10:00am tomorrow. Because if it's B, I'm curious why the headline on your web site says: "Built on code. Driven by AI. Engineered for scale”. The reason I'm curious is because like you were more attracted to B, your audience would be more attracted to: "You can’t build tomorrow’s software on yesterday’s stack, but we're not yesterday's stack". People don't buy the best product. They buy the best product they understand. #Wordsmatter

Thought-provoking read from Sakara Digital Our new blog series, Code Without Compassion, explores what happens when automation replaces empathy in workforce decisions. Part 1 looks at Amazon Flex and the human cost of algorithmic management. https://lnkd.in/eEyibm4n  

75% of Amazon sellers are already using automation. And in 2025, those who aren’t are falling behind. Amazon just launched Amelia, its AI assistant that helps sellers detect operational issues, stock drops, and compliance alerts in real time. External tools like SellerPulse and Sellerboard Alerts now send instant notifications when you lose the BuyBox or your price changes. → Recent case: a wholesale seller recovered lost sales in under 48 hours after activating automatic inventory variation alerts. → Result: less time checking dashboards, more time selling. The future isn’t about reacting. It’s about anticipating issues before they cost you sales. Comment “FIX” and I’ll send you the full guide on automating Amazon problem detection.

🏗️ Why DDD Matters in AI-Driven Businesses Have you ever wondered why your banking app feels smooth for payments, but messy for things like support tickets? That’s because some systems align with Domain-Driven Design (DDD), and some don’t. 👉 DDD ensures developers, domain experts, and AI systems speak the same language. 👉 It prevents messy codebases where every new feature feels like “jamming a square peg into a round hole.” 💡 Example: Amazon separates Catalog (list of products) from Checkout (orders + payments). That’s a Bounded Context. Healthcare AI separates diagnostics from insurance claims. 🚀 In an AI world, DDD ensures new models and services integrate seamlessly with business processes. ❓ Question: Did you realize every time you check out on Amazon, you’re actually moving across different Bounded Contexts? #DomainDrivenDesign #DDD #AI #Architecture #Amazon

As organisations continue to leverage Large Language Models (LLM’s) in a wider range of use cases in their business, choice of specialisation, speed and cost is proving to increase the pace of applications. What is not negotiable is enterprise grade security, safety and data privacy. This is why many of them are turning Amazon Bedrock. However what we are also observing is that open-weight models improve greater control around fine tuning them specifically for your use cases, providing greater transparency. This is why we made two new models available: Qwen3, from Alibaba which delivers model options for sophisticated coding and general reasoning. And DeepSeek-V3.1 which delivers exceptional performance across math, coding and agentic tasks. Read more here 👉 https://lnkd.in/gd6hC_SE

Walmart + OpenAI It’s not about empowering customers it’s about retaining transaction control in a world where AI agents might otherwise buy anywhere. If shopping shifts from you typing into Amazon or Google to your personal AI choosing where to buy, the retailers lose the interface. So they’re racing to: expose APIs to those agents, brand the term “agentic commerce,” and keep their ecosystem relevant when humans stop doing the clicking. It’s defensive, not visionary.

The way we shop is evolving. As AI integrates deeper into commerce, it’s not just about convenience, it’s about personalization at scale. Already a commerce giant, Amazon is well-positioned with its AI-driven algorithms (e.g., product recommendations, Alexa). The shift toward impulse buys and routine essentials via AI-optimized platforms aligns with Amazon’s ecosystem, potentially widening its lead over Google.

DataDoe just leveled up and Amazon sellers are already feeling the speed. If you manage Amazon accounts or clients, this update changes your week. Here’s what’s new inside DataDoe 👇 👉 Chat got smarter. Compare multiple metrics on one chart, finally see ACOS vs spend side by side. Auto-query fixing means you can type in anything, and DataDoe understands what you meant. 👉 Automations got serious. Build “if X then Y” flows directly in chat, no code needed. Schedule daily or weekly triggers. Stop, re-run, or edit actions without rebuilding workflows. Agencies can now manage all client accounts in one place. 👉 Reports got bigger. Export TSV or XML files, no size limits. Cleaner report names, no date picker bugs, faster generation. You can now handle serious Amazon data. 👉 Platform upgrades. New Home and Prompt Library to discover use cases faster. Data limits raised to 15M rows by default. DataDoe is no longer just a dashboard. It’s your AI operator for Amazon - spotting problems, suggesting fixes, and automating everything that slows you down. Early users are already running proactive alerts and multi-account automations. 👀