Operations | Monitoring | ITSM | DevOps | Cloud

CapCut for Real Estate: AI Voice Narration for Property Tours

Listing videos have proved a potent display of property available on the internet; however, not all videos with good frames cut through the market. The CapCut Desktop Video Editor has been designed as an all-in-one editing tool that enables real estate professionals to design a property tour with AI voiceover, action transitions, and high-definition pictures. CapCut gives the opportunity to create high-quality, compelling virtual tours even in the case of absence of a professional narrator and a studio where it is possible to shoot.
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When AI Becomes the Judge: Understanding "LLM-as-a-Judge"

Imagine building a chatbot or code generator that not only writes answers - but also grades them. In the past, ensuring AI quality meant recruiting human reviewers or using simple metrics (BLEU, ROUGE) that miss nuance. Today, we can leverage Generative AI itself to evaluate its own work. LLM-as-a-Judge means using one Large Language Model (LLM) - like GPT-4.1 or Claude 4 Sonnet/Opus - to assess the outputs of another. Instead of a human grader, we prompt an LLM to ask questions like "Is this answer correct?" or "Is it on-topic?" and return a score or label. This approach is automated, fast, and surprisingly effective.

Can Agentic AI Fix the Chatbot Fatigue in the CX Industry? A Strategic Analysis for CXOs

Belinda Parmar, CEO of The Empathy Business, in a recent article with Financial Times, said, Customer service has undergone a significant transformation in recent years. Where success was once measured by resolution speed and cost efficiency, today’s customers expect far more. They seek personalized interactions, contextual awareness, and a genuine human touch, delivered alongside fast, reliable support.

With AI, You're Gonna Have to Manage Your (Massive) Energy Use in SPM

Forget boring spreadsheets. Strategic portfolio management (SPM) isn't just about ticking boxes. It’s the big boss plan that makes sure every penny spent and every project your company starts points towards the main goal. It's your company's smart GPS, guiding you through the AI energy maze. When it comes to AI's power hunger, SPM is a knight in shining armor. It helps leaders get smart, making sure they grab all the fancy tech without trashing the world.

Smarter debugging with Sentry MCP and Cursor

Debugging a production issue with Cursor? Your workflow probably looks like this: Alt-Tab to Sentry, copy error details, switch back to your IDE, paste into Cursor. By the time you’ve context-switched three times, you’ve lost your flow and you’re looking at generic suggestions that don’t show any understanding of your actual production environment or codebase.

Semantic Caching: What We Measured, Why It Matters

Semantic caching promises to make AI systems faster and cheaper by reducing duplicate calls to large language models (LLMs). But what happens when it doesn’t work as expected? We built a test environment to find out. Through a caching system, we evaluated how semantically similar queries would behave. When the cache worked, response times were fast. When it didn’t, things got expensive. In fact, a single semantic cache miss increased latency by more than 2.5x.

Is on-prem the top choice to run AI?

‎‎Subscribe. Fuel your curiosity. In this episode, we break down what we’ve learned from teams running AI at scale, and why on-premises infrastructure is making a strong comeback. We’re seeing a shift: performance, cost control, data sovereignty, and platform flexibility are driving conversations about on-prem strategies for AI. No one-size-fits-all answers, but if you’re building or scaling AI, this might help you think a few steps ahead.

Are you running AI the smart way?

Data locality: AI models often rely on large datasets. Locating compute close to the data reduces transfer times and improves training performance. Latency sensitivity: Real-time AI applications, like recommendation systems or edge analytics, depend on low-latency environments. This can be more easily tuned in private or hybrid setups. Hardware specialization: Some AI workloads benefit from custom hardware like GPUs or TPUs. Private cloud allows more control over this, while public cloud offers broader access but less customization.

Beyond AI hype: put reliability at the forefront

Reliability is a constant for every technology, whether it’s cloud, microservices, or AI. Full transcript:  Just a few years ago everybody was screaming about microservices, "That's the wave of the future," and now everybody's looking at AI. No matter what the change in technology hot topic is, your reliability should still be at the forefront of everything that you're doing.