SolarWinds AI Launches to Transform IT Service Management
Generative AI engine developed under new AI by Design framework debuts in company’s premier ITSM solution
SolarWinds AI is first being introduced in SolarWinds Service Desk, the company’s world-class IT service management (ITSM) solution for improving IT outcomes, service delivery, and employee satisfaction. SolarWinds AI powers a transformative new generative AI feature in Service Desk, designed to supercharge agent workflows and facilitate empowered, high-performing IT teams to resolve tickets in minutes rather than hours or days. This accelerated remediation process helps create a world-class experience for employees across the organization by minimizing downtime and outages.
Powered by large language models (LLMs) and proprietary algorithms, SolarWinds AI in Service Desk instantly summarizes complex ticket histories, provides suggested agent responses to inquiries, and generates real-time recommended steps for resolving issues. The company also plans to introduce SolarWinds AI throughout its suite of observability and IT management solutions, adding a new digital partner for DevOps, SecOps, database teams, and beyond.
“In creating SolarWinds AI, we leveraged our long history of engaging with the IT community to build an AI system that could act as a valued partner to IT pros in their everyday lives and reimagine the productivity, efficiency, and innovation they’re capable of,” said
AI by Design is a rigorous framework for creating secure, productive, and enduring AI-driven solutions, guided by four key principles:
- Privacy and Security: To help ensure unparalleled data safety, SolarWinds AI is designed to secure personal data collection, storage, use, and protection through robust measures, like role-based access control (RBAC), multi-factor authentication (MFA), privileged access management (PAM), and anonymization techniques. Sensitive customer data does not pass through external large language models (LLMs), and SolarWinds AI improves based on usage patterns and organizational needs without compromising data privacy.
- Accountability and Fairness: SolarWinds AI proactively includes humans in training and testing to oversee AI-guided decision-making processes to avoid biases. It captures and addresses negative user experiences through robust feedback and validation mechanisms, ensuring that human judgment plays a crucial role throughout the AI lifecycle.
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Transparency and Trust : To provide confidence in the outcomes of AI-driven processes, SolarWinds AI features a well-defined explainability pipeline to demonstrate the rationale behind AI-generated actions. This enables continuous refinement based on the customers’ evolving needs and helps demystify the process for AI decisions and outputs. - Simplicity and Accessibility: SolarWinds AI is built into the company’s user-friendly product interfaces to help ensure the continuation of regular workflows and existing user procedures, behaviors, and practices.
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This press release contains “forward-looking” statements, which are subject to the safe harbor provisions of the Private Securities Litigation Reform Act of 1995, including statements regarding future features and functionality. These forward-looking statements are based on management's beliefs and assumptions and on information currently available to management. Forward-looking statements include all statements that are not historical facts and may be identified by terms such as “aim,” “anticipate,” “believe,” “can,” “could,” “seek,” “should,” “feel,” “expect,” “will,” “would,” “plan,” “intend,” “estimate,” “continue,” or similar expressions and the negatives of those terms. Forward-looking statements involve known and unknown risks, uncertainties and other factors that may cause actual results, performance or achievements to be materially different from any future results, performance or achievements expressed or implied by the forward-looking statements. Factors that could cause or contribute to such differences include but are not limited to, the risks and uncertainties described more fully in documents filed with or furnished to the
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