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Top 5 Companies Streamlining Reverse Logistics for Tech Manufacturers

If you work in hardware manufacturing or IT management, you know the sinking feeling of seeing a palette of returned equipment sitting on a loading dock. In the past, that palette was just trash, a cost center you tried to ignore. But in 2026, that palette is a gold mine disguised as a headache.

How One Tool Can Replace Five and Streamline PDFs for Daily Operations

Running a company used to mean everyone was in the same building, but that is rarely the reality anymore. Modern operations teams now work across different regions and time zones as a standard part of their day. In this distributed environment, PDFs remain the primary format for everything from contracts and internal manuals to reports and documentation. However, even though they are everywhere, they often cause significant friction that slows teams down. This guide focuses on common PDF hurdles and how you can use a good PDF tool like UPDF to streamline your PDF operations.

Agentic AI Essentials: Your Guide to the Future of Automation

To mark the launch, we’re publishing Agentic AI Essentials, a four-part series to help organizations navigate the reality of agentic AI adoption. Across the series, we’ll look at the questions that matter most: what’s real versus hype, how to avoid adoption pitfalls, how to measure ROI, and how roles will evolve once agents are onboarded. Here’s a sneak peek at what’s in store.

Finetuning Gemma 3 on private data with Unsloth and CircleCI

Fine-tuning Large Language Models (LLMs) on private, domain-specific data can unlock significant value for your specific use case. When done correctly, you can create AI apps that understand your organization’s unique context. These apps can speak your brand’s voice and deliver remarkably accurate results that general models cannot match. However, finetuning is not always the right solution. Many teams rush into this complex technique without exploring simpler alternatives first.

Poisoning the Well: The Invisible Danger in Your AI Supply Chain

Welcome to the AI research bites. This series of short and informative talks showcases cutting-edge research work from ServiceNow AI Research team. The AI Research Bites are open to all, especially those interested in keeping up with the fast-paced AI research community.

Build custom apps in seconds with conversational AI in App Builder

Using a drag-and-drop interface, engineering teams can create apps that support troubleshooting, improve day-to-day operations, and offer self-service access without leaving Datadog. With the new conversational AI feature, teams can turn an idea into a working app in seconds. Watch the video to see how it works..

DLP: The Key to Secure K8s Testing #speedscale #dlp #kubernetes #devops #testing

Testing with production traffic doesn't have to be a security risk. Engineers often avoid production data because of sensitive info like passwords, tokens, and PII. But legacy test data management is too static for modern, fast-changing payloads. Enter the Speedscale Streaming DLP Engine. It automatically detects and redacts sensitive data in real time as it's captured from your environment. You get the realism of production traffic without the risk of a data breach.

Beyond the Hype: Building a Future-Proof Foundation for the AI-Native Enterprise

We are witnessing a fundamental transformation in how software is built. The industry has moved beyond the experimental phase of Machine Learning Operations and entered a complex new reality: the era of the AI Software Supply Chain. The adoption metrics confirm this shift is irreversible. Google reports that 90% of tech workers are now using AI as part of their daily work. Similarly, McKinsey data reveals that 88% of organizations use AI in at least one business function.

How to Ensure AI-Generated Code is Reliable with Runtime Context

TLDR: AI coding assistants have sped up code delivery, but created a validation gap. Historic telemetry and static analysis cannot predict the behavior of unfamiliar, high-volume code. Lightrun’s Runtime Context MCP closes that gap, allowing AI assistants to verify behavior before it breaks, and resolve issues in real time.