Operations | Monitoring | ITSM | DevOps | Cloud

Agentic AI in RevOps: How Leading Media and Platform Companies Maximize Outcomes Efficiently

Advertising-driven revenue models have become increasingly appealing to businesses across various sectors in recent years. This approach has gained significant traction among retailers, grocers, and commerce intermediaries seeking to diversify their income streams. However, the rapid evolution of these markets has often led to operations marked by manual interventions, disjointed systems, and fragmented data workflows.

Best Practices for Ephemeral Environments: Auto-Anonymizing PostgreSQL Data for AI & Devs

AI coding and development thrive in real, production-like environments—not just sandboxes with dummy data. But here’s the challenge: real data often includes sensitive info like PII, financials, or healthcare records, all governed by strict regulations like GDPR and HIPAA. How do you balance security, compliance, and speed? In this webinar, we dive into practical solutions with a live demo featuring Bunnyshell and Xata.io.

AI On A Budget: Low-Cost Strategies For Running AI In The Cloud

AI costs can spiral out of control before you know it. One day you’re building an AI feature that promises to bring in a solid chunk of revenue for the company. The next day you’re obsessing over an astronomically high cloud bill that will significantly eat into your profits — or consume them entirely. To help you solve this problem, we brought in Jeremy Daly, Director of Research (and AI cost management guru) at CloudZero.

The Future of Customer Experience: How can Agentic AI reverse declining CX trends?

The state of customer experience (CX) in the United States has reached a critical juncture. Findings from Forrester's 2024 US Customer Experience Index (CX Index) revealed a concerning trend: a significant decline in overall CX quality, marking the third consecutive year of deterioration. CX quality has reached an all-time low since 2016, with nearly 40% of brands experiencing a decline.

Can Data Centers Keep Up with AI? Hyperview CEO Breaks It Down

With the rise of AI, data centers are becoming a bigger part of our everyday lives. But this growing reliance also brings up serious concerns about energy use and the environment. On Ticker’s business news show, Hyperview CEO Jad Jebara discussed how AI is driving data center operators to rethink how they handle these energy-hungry workloads while working toward sustainability goals.

Machine learning vs AI: Key differences and how they work together

Machine learning (ML) and artificial intelligence (AI) are often used interchangeably in tech discussions, yet they represent distinct concepts with important differences. While AI refers to the broader field of creating machines capable of intelligent behavior that mimics human capabilities, machine learning is a specific subset of AI focused on developing algorithms that allow computers to learn from and make predictions based on data.

Decoding AI-led event correlation for mastering modern IT management

"The whole is more than the sum of its parts," said Aristotle. This quote fits the amazing world of modern IT, where several intricate, interwoven, and intensely dynamic ecosystems come together. Today, every component, from applications and microservices to networks and databases, interacts dynamically. To ensure seamless operations, IT teams are expected to decode the language of these interactions: events and incidents.