Operations | Monitoring | ITSM | DevOps | Cloud

How AI Agents Are Changing ITSM Faster Than We Think | Motadata Webinar

AI is transforming ITSM beyond co-pilots with autonomous AI agents that can understand, decide, and act. In this webinar, discover how AI agents are reducing manual workloads, accelerating incident resolution, improving service quality, and enabling intelligent service operations. Learn real-world use cases, key implementation strategies, and how organizations can move from reactive support to proactive, AI-driven IT service management. Watch now to explore the future of smarter, faster, and more efficient ITSM.

The Business Benefits of a Strong Asset Management Strategy

Every business depends on valuable assets, from equipment and machinery to buildings and technology. How these assets are managed has a direct impact on productivity, operating costs, and long-term growth. Without a clear strategy, businesses may face unexpected breakdowns, rising maintenance expenses, and poor use of resources. A strong asset management strategy helps organizations track asset performance, plan maintenance, extend asset life, and make better investment decisions. It also improves efficiency and supports smarter business planning.

Best 7 GPU VPS Provider for Machine Learning (ML) and AI

There is no reason to buy a GPU. That's unless you train your model or do serious image/video manipulation. A GPU server costs several times more than a CPU VPS for the same month. "Nine out of ten requests for a GPU server for AI actually need a mid-size CPU VPS. They are serving a model, not training one. Match the hardware to the task at hand. Save money. Don't compromise on performance.".

Why Interactive Vending Machines Are Becoming the Next Big Business Opportunity

Businesses are always looking for fresh ways to draw in customers, raise revenue, and offer experiences people will remember. Interactive vending machines are among the fastest-growing developments in automated retail, bringing together convenience, technology, and entertainment in one system. Traditional machines mainly dispense products; interactive models go further by engaging users with touchscreens, artificial intelligence, digital payment options, and personalized experiences.

Install AURA to Debug Incidents Using an Open Source SRE Agent

AURA is a fully open-source agentic harness built for SRE and production operations work. In this walkthrough, Mezmo forward deployed engineer Jeff iinstalls AURA on a local desktop, runs `aura init` to generate the config and connect it to an Anthropic Sonnet model, then wires in a Grafana MCP server pointed at his homelab. He hands AURA a live incident: a set of addressable LED lights that stopped responding to Home Assistant.

How to prove the business value of AI

Proving AI business value means sorting every AI investment into one of four buckets - revenue growth, cost avoidance, productivity gain, or risk reduction - then tracking spend at the unit level (per feature, customer, or team) so each dollar has a traceable return. Most companies measure one bucket well and leave the rest unattributed. That gap is why the same AI deployment can look like a $40M win and a public reversal at the same time.

Gemini Models are Misunderstood

Recently, Google released a couple new Gemini models. They were Gemini 3.6 Flash, 3.5 Flash Lite, and 3.5 Flash Cyber. Many people on the internet roasted Gemini Flash and Flash Lite for their less-than-frontier performance. This makes sense when you consider that OpenAI and Anthropic have been sparring back and forth for first place for quite a while but Gemini almost never gets that first place position. After all, this is Google we are talking about.

The New AI Mandate: Smarter Usage, Lower AI Compliance Risk, Better Outcomes

For the last two years, enterprise AI strategy has largely revolved around one message: use AI as much as possible. CIOs encouraged experimentation, CFOs approved budgets, and organizations pushed employees to adopt tools like ChatGPT, Claude, Copilot, and Gemini in the hope that productivity gains would naturally follow. The prevailing assumption was that simply increasing usage would accelerate innovation and unlock efficiency across the organization. But the enterprise conversation is changing quickly.