Vitria Technology

Technology Consulting/Tech Services - Menlo Park, CA, US

Vitria Technology Details

Move from Analyzing Data to Automating Actions. VIA AIOps, a next generation application for fault, performance and change management accelerates the detection and resolution of service-impacting issues across the technology stack. VIA leverages data science to reduce alarm noise, detect earlier, uncover the root cause and prescribe actions. VIA is a non-disruptive value multiplier to existing monitoring tools and processes by integrating with and correlating across already deployed systems.Across service layers, VIA uses advanced analytics, AI, and machine learning to move from noise reduction and fault detection to service assurance and predictive analytics. Ingesting and enriching both asynchronous events and time series data in real time, VIA addresses fault and performance management within a single AIOps application. VIA creates intraday seasonal baselines to define faults faster than simple threshold boundary conditions. Learning application and service dependencies, VIA creates rich metadata for use in correlation and affinity analysis that accelerate diagnostics. AI-powered analysis determines if events and signals across operating silos are related and whether they should be treated as a single incident or separately. Symptoms are distinguished from probable cause and the impacted populations defined.Vitria is a company with a long history of innovation. The company celebrates twenty plus years of providing solutions that have transformed business process management and application delivery across the distributed enterprise. Vitria has 20+ years of experience in model-driven compute environments, process automation, complex event processing and big data analytics.Learn more by visiting www.vitria.com

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Website: vitria.com
Employees: 250 - 499
HQ: 650-460-8600
Location: Menlo Park, CA, US
Revenue: 10 - 20 Million
IoT Analytics Complex Event Processing Operational Intelligence Business Activity Monitoring Automation Real-Time Analtyics Historical Analytics Predictive & Prescriptive Analytics Big Data Analytics Visual Analytics Real-Time Analytics Real-Time Operational Visibility Advanced Anomaly Detection Incident Life-Cycle Automation Dynamic Failure Prediction Digital Operations Predictive Analytics Industrial IoT Machine Learning Root Cause Analysis Service Health Key Trend Analysis Change Management Model driven low code development managed growth augmented intelligence customer experience service operations SaaS Information Technology and Services Computer Hardware Software Information Technology
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