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ScienceLogic Expands AI Platform with Skylar Offerings

ScienceLogic unveiled its reimagined portfolio of offerings within the ScienceLogic AI Platform. 

Aligned with the company’s Agentic AI roadmap, Skylar™ One, Skylar™ AI, Skylar™ Automation, and Skylar™ Compliance showcases the power of the ScienceLogic AI Platform to help IT teams resolve issues faster, operate with greater resilience and prepare for the next era of IT innovation.

“The evolution of our portfolio into the Skylar offerings shows how our platform has progressed to meet the needs of our customers in an increasingly agentic world,” said Michael Nappi, chief product officer at ScienceLogic. “By unifying observability, automation, compliance, and AI on the ScienceLogic AI Platform, we’re helping IT leaders cut through complexity and move faster. Built on the platform our customers trust, Skylar brings new technologies that enable a far more automated state of IT operations.”

Together, the Skylar offerings form the portfolio of solutions built on the ScienceLogic AI Platform—the engine behind intelligent, outcome-driven IT operations.

  • Skylar One: (formerly SL1®) is the foundation of the ScienceLogic AI Platform, delivering unified, service-centric observability across hybrid and multi-vendor environments. It connects and synthesizes fragmented data silos, accelerates root cause analysis, and optimizes operations at scale. Includes Skylar One Studio (formerly SL1 Studio) for out-of-the-box monitoring integrations via ScienceLogic PowerPacks and flexible, customizable observability.
  • Skylar Automation: (formally PowerFlow™) is the low-code orchestration engine that connects insights IT ecosystems – from ITSM, CMDBs to collaboration and cloud platforms – automating processes from detection to resolution and eliminating manual toil.
  • Skylar AI: (name retained) is the intelligence layer of the ScienceLogic AI Platform, powering correlation, prediction, and proactive remediation through Agentic AI. It includes Skylar Analytics for unsupervised prediction and detection, and Skylar Advisor for plain-language guidance and safe, executable actions to reduce MTTR.
  • Skylar Compliance: (formerly Restorepoint™) delivers centralized backup, recovery, and policy enforcement across multi-vendor infrastructures, ensuring resilience and minimizing downtime.

"With Skylar at the center of our platform, we’re moving organizations closer to a future where AI and agentic automation eliminate friction, accelerate remediations and free teams to innovate," said Dave Link, CEO and co-founder of ScienceLogic. "This portfolio evolution marks a bold step forward for the IT industry—and a new era for ScienceLogic"

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ScienceLogic Expands AI Platform with Skylar Offerings

ScienceLogic unveiled its reimagined portfolio of offerings within the ScienceLogic AI Platform. 

Aligned with the company’s Agentic AI roadmap, Skylar™ One, Skylar™ AI, Skylar™ Automation, and Skylar™ Compliance showcases the power of the ScienceLogic AI Platform to help IT teams resolve issues faster, operate with greater resilience and prepare for the next era of IT innovation.

“The evolution of our portfolio into the Skylar offerings shows how our platform has progressed to meet the needs of our customers in an increasingly agentic world,” said Michael Nappi, chief product officer at ScienceLogic. “By unifying observability, automation, compliance, and AI on the ScienceLogic AI Platform, we’re helping IT leaders cut through complexity and move faster. Built on the platform our customers trust, Skylar brings new technologies that enable a far more automated state of IT operations.”

Together, the Skylar offerings form the portfolio of solutions built on the ScienceLogic AI Platform—the engine behind intelligent, outcome-driven IT operations.

  • Skylar One: (formerly SL1®) is the foundation of the ScienceLogic AI Platform, delivering unified, service-centric observability across hybrid and multi-vendor environments. It connects and synthesizes fragmented data silos, accelerates root cause analysis, and optimizes operations at scale. Includes Skylar One Studio (formerly SL1 Studio) for out-of-the-box monitoring integrations via ScienceLogic PowerPacks and flexible, customizable observability.
  • Skylar Automation: (formally PowerFlow™) is the low-code orchestration engine that connects insights IT ecosystems – from ITSM, CMDBs to collaboration and cloud platforms – automating processes from detection to resolution and eliminating manual toil.
  • Skylar AI: (name retained) is the intelligence layer of the ScienceLogic AI Platform, powering correlation, prediction, and proactive remediation through Agentic AI. It includes Skylar Analytics for unsupervised prediction and detection, and Skylar Advisor for plain-language guidance and safe, executable actions to reduce MTTR.
  • Skylar Compliance: (formerly Restorepoint™) delivers centralized backup, recovery, and policy enforcement across multi-vendor infrastructures, ensuring resilience and minimizing downtime.

"With Skylar at the center of our platform, we’re moving organizations closer to a future where AI and agentic automation eliminate friction, accelerate remediations and free teams to innovate," said Dave Link, CEO and co-founder of ScienceLogic. "This portfolio evolution marks a bold step forward for the IT industry—and a new era for ScienceLogic"

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Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

Kubernetes has become the backbone of cloud infrastructure, but it's also one of its biggest cost drivers. Recent research shows that 98% of senior IT leaders say Kubernetes now drives cloud spend, yet 91% still can't optimize it effectively. After years of adoption, most organizations have moved past discovery. They know container sprawl, idle resources and reactive scaling inflate costs. What they don't know is how to fix it ...

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

On September 16, the world celebrated the 10th annual IT Pro Day, giving companies a chance to laud the professionals who serve as the backbone to almost every successful business across the globe. Despite the growing importance of their roles, many IT pros still work in the background and often go underappreciated ...

Artificial Intelligence (AI) is reshaping observability, and observability is becoming essential for AI. This is a two-way relationship that is increasingly relevant as enterprises scale generative AI ... This dual role makes AI and observability inseparable. In this blog, I cover more details of each side ...