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From Data Analytics to AI: The Technology Behind Modern Fraud Detection

From Data Analytics to AI: The Technology Behind Modern Fraud Detection

Aug 13, 2026 By OpsMatters In OpsMatters
A supplier changes its bank details at 3:12 p.m. Three invoices arrive before 5:00, each just below the level requiring senior approval. That evening, an unfamiliar device accesses the payment account. None of those events proves fraud. Together, they form the kind of pattern modern detection systems are built to recognise.
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AI and Real-World Evidence: The Growing Role of Intelligent Systems

AI and Real-World Evidence: The Growing Role of Intelligent Systems

Aug 13, 2026 By OpsMatters In OpsMatters
A modern incident rarely leaves one decisive record. It leaves a data field. A vehicle stores speed and brake input. A phone preserves motion and location signals. Cameras capture visible movement, while cloud platforms log account activity. Artificial intelligence can connect these fragments and build a timeline that a human investigator can test. Machines have not become witnesses. They have become tools for comparing what different systems recorded, exposing conflicts, and showing where the evidence remains incomplete.
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The Technology Behind the Rapid Growth of On-Demand Home Services

The Technology Behind the Rapid Growth of On-Demand Home Services

Aug 13, 2026 By OpsMatters In OpsMatters
A leaking pipe may look like a simple booking problem. For the platform receiving the request, it is a live decision problem involving diagnosis, skills, distance, time, price, identity, risk, and incomplete information. The rapid growth of on-demand home services did not come from placing a calendar inside an app. It came from making field work machine-readable enough to classify, optimize, monitor, and improve.
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Build and Launch AI Agents from Your Splunk Workflows

Aug 12, 2026 By Splunk In Splunk
Introducing the Splunk Agent Launchpad! Let’s face it—your team is busy. Between managing alerts, digging through investigations, and constant context-switching, it’s hard to stay ahead of the noise. What if you could turn your existing operational knowledge into custom AI agents that do the heavy lifting for you? And the best part? No coding required. Watch this exclusive look at the Splunk Agent Launchpad. We’re showing you how to build, deploy, and manage AI agents that help you investigate, enrich, summarize, and act—all without leaving the Splunk environment you already know and trust.
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Argo CD Deployment Failed: AI SRE Agent AURA Finds and Fixes It

Aug 12, 2026 By Mezmo In Mezmo
A deployment fails validation and the sync stops. Argo CD hands the report to AURA, which finds the wrong version, fixes it, and re-runs the sync. Normally, a failed sync means a person opens the application, reads the hook logs, and works out which value is wrong. Here, the sync fail hook sends AURA a short failure report and an incident ID over the agent-to-agent protocol, then exits. It does not say how to investigate or what to change.
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cloudzero

How to build the business case for AI

Aug 12, 2026 By Doug Bonderud In CloudZero
A strong AI business case ties a specific goal to a measured outcome and a fully-loaded cost. Most fail because they skip one of the three: no clear mandate, an over-broad "AI fixes everything" scope, or a cost estimate that ignores adaptation and error-correction. Build it in six steps: define goals, identify uses, break work into tasks, evaluate models, assess total cost, then launch and refine. Most companies are now spending on AI. Far fewer can show what they got back.
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cloudzero

How to right-size your existing Claude skills

Aug 12, 2026 By Djo Lopez In CloudZero
You shipped a skill. It worked. You closed the tab. That’s the whole problem. Model choice is a decision you make once, at the moment you’re least equipped to make it: before the skill is even authored. Then you never revisit it, because the skill stopped being interesting the day you got it working. So go back and check. Here’s how.
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pagerduty

AI Is Outpacing Code Review. Here's How to Catch Up (Without Slowing Down)

Aug 12, 2026 By Stephanie Muñiz In PagerDuty
In a 2025 analysis spanning over 100 large language models, Veracode found that nearly half (45%) of AI-generated code causes known security issues and vulnerabilities. Novel risks are being introduced into your operations systems faster than humans can manage or review. At the same time, studies suggest that human review isn’t all that effective, especially beyond 400 lines of code. But AI-generated code isn’t inherently bad. It just doesn’t always work across your whole system.
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