smartQED Launches Public Beta of its SaaS Product for Accelerated Incident Resolution
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smartQED, Inc. is launching a public Beta for its SaaS product for rapid incident resolution. The company focuses on providing innovative solutions that bring Enterprise IT Ops/DevOps incidents to quick resolution, thereby improving the availability and reliability of services.
San Mateo, CA, Feb 13, 2020 -- smartQED today announced the public Beta release of its SaaS product, which features a team-centric collaborative workspace for complex problem investigations, and a powerful recommendation engine that assists IT Operations and DevOps teams in resolving incidents efficiently and reliably.
Announcing the launch, smartQED CEO, Julie Basu said, “In today’s technology-driven world where millions of users rely on 24x7 availability of IT systems, site reliability has become mission-critical. Operations teams are under extreme pressure to provide rapid responses, effective resolution of problems, and timely restoration of service. At the same time, enterprise IT ecosystems have evolved into complex architectures of interacting infrastructure and agile applications. When a monitoring system detects an incident, typically multiple teams and subject matter experts (SMEs) have to come together to identify, analyze, and resolve the underlying causes. During this process, teams can greatly benefit from smartQED’s self-learning visual tools that provide a structured view of the problem investigation for effective collaboration, clear communication, and faster resolution compared to text-based tools.”
Visual Collaborative Workspace
smartQED provides a visual, in-context collaborative workspace with patent-pending technology that allows investigation teams to reach a shared understanding of an incident very quickly. Using the workspace, teams can create cause analysis maps on-the-fly or from pre-defined templates to systematically track complex investigations, thus streamlining communications while enabling efficient onboarding and hand-over between shifts during the resolution process. The tool also eliminates laborious status reporting with the help of auto-generated reports that provide transparency and visibility into the investigation progress through concise and timely updates to all stakeholders.
ML-based Recommendation Engine
The smartQED product has a built-in automated knowledge capture and recommendation engine. This powerful engine is based on smartQED’s innovative natural language processing and ML technologies. It uses data from prior incidents as captured through the visual workspace, and is also designed to analyze and aggregate known issues from public repositories and accumulated enterprise knowledge sources. These automated recommendations can drastically reduce the MTTR and help investigation teams find causes and remediation/recovery steps for new problems rapidly.
Terry Gallagher, a seasoned Crisis Manager for large enterprises and Head of Customer Solutions at smartQED, says “More than 80% of an organization’s knowledge articles are never opened, much less used. Operations teams invest too much energy writing KAs which are not useful, especially in high pressure situations. Our smartQED product provides succinct recommendations for probable causes, greatly simplifying knowledge reuse from prior incidents.”