ScienceLogic announced the availability of Skylar Advisor™, an AI-native advisor designed to help IT teams turn overwhelming data into confident, valuable outcomes.
Skylar Advisor is AI-native by design, combining real-time observability data with customer-owned knowledge to reason across IT environments and delivering guidance that is transparent, explainable, and verifiable.
Skylar Advisor eliminates the manual stitching of alerts, tickets, and tribal knowledge. It transforms enterprise data and customer-owned documentation into evidence-backed recommendations that teams can inspect, validate, and trust.
Skylar Advisor introduces a more proactive operating model for IT, one where AI doesn’t just surface insights, but prioritizes and guides actions.
"IT teams are drowning in data but starving for insight," said Dave Link, CEO and co-founder of ScienceLogic. "Skylar Advisor applies AI reasoning directly to operational reality – not abstract prompts or generic models. It automates the analysis and guidance that once depended on human intuition. This helps organizations act faster, reduce risk, and innovate with confidence."
Part of the ScienceLogic AI Platform™, Skylar Advisor functions as an AI-native partner that understands IT context, explains issues in plain language, and guides teams toward the most effective next steps. Rather than reacting to individual alerts, Skylar Advisor continuously reasons across telemetry, topology, and historical knowledge to surface what matters most and why.
Skylar Advisor proactively delivers insights and guidance across the lifecycle of IT operations. It supports professionals at every level, enabling junior engineers to resolve issues with confidence while allowing senior engineers and SREs to focus on higher-value initiatives such as optimization, automation, and innovation.
Skylar Advisor is powered by a knowledge-centric architecture. It combines agentic orchestration with automated knowledge capture and state-of-the-art retrieval accuracy, deployable anywhere. It combines real-time observability with curated enterprise knowledge to deliver verifiable, actionable intelligence. Every recommendation is grounded in evidence, with explicit traceability to the underlying data and documentation that informed it.
Key capabilities include:
- Advisories: Automatically detect, summarize, and explain the most critical problems buried within event floods, helping teams prioritize what matters most and why.
- Ask Skylar: Provide instant, context-aware answers through a conversational interface grounded in enterprise knowledge to accelerate investigation and execution.
- Persona Wizard: Adapt tone, depth, and format of guidance based on user role from L1 engineers and SREs to executives ensuring relevance and clarity.
- Knowledge Corpus: Unify telemetry with trusted knowledge sources, forming the foundation that powers guidance while maintaining governance and control.
- Automatic Knowledge Generation: Capture investigation steps and verified fixes to continuously create accurate, reusable knowledge base content.
- Verifiable Insights: Ensure all guidance is evidence-backed, citing the exact data and documents used for traceability and assurance.
"As IT environments continue to scale, relying on people to manually connect alerts, tickets, and documentation doesn’t work," said Michael Nappi, Chief Product Officer at ScienceLogic. "Skylar Advisor automates how operational knowledge is captured, interpreted, and applied, helping teams move faster and make better decisions without adding risk."
Skylar Advisor is a core intelligence component of the ScienceLogic AI Platform, which also includes Skylar One™ (formerly SL1) for observability, Skylar Automation™ for action, Skylar Compliance™ for assurance, and Skylar Analytics™ for deeper metric insights. Together, the platform delivers service-centric observability, AI-driven operations, and intelligent automation aligned directly to business outcomes.
Skylar Advisor helps IT organizations move beyond reactive monitoring to a more proactive, resilient operating model by embedding intelligence directly into daily operations, turning enterprise data and institutional knowledge into faster decisions and better outcomes.
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