Use Cases and Results

Improved service availability by 60% and reduced staffing requirements by 50%.

Use Cases and Results

Reduced MTTR by 40% for service disruption and by 80% for degradation issues.

Use Cases and Results

92% of incidents were detected prior to customer impact.

Use Cases and Results

The failure rate was reduced by 28% avoiding the addition of 20 full-time staff at a cost of $2.3 million.

Enhance customer experience, lower cost, and improve operational efficiency with VIA AIOps

VIA AIOps enables a new service assurance operating model and a new way of working through automation powered by real-time analytics, artificial intelligence, and machine learning.

North American MSO Enables Intelligent Operations with Natural Language Processing and GenAI-Based ChatOps

Breakdown Operational Silos and Improve Response and Resolution Time

  • Eliminates miscommunication and resulting ping-pong issue movement from one fix team to another
  • Integrates with existing communication tools
  • Enables AIOps info access without need to onboard a new UI
  • Reduces miscommunication & fosters transparency
  • Find root cause and the right fix quickly accelerating both incident response and resolution time

Tier 1 MSO
Uses GenAI to Empower Likely Fix Recommendations

Automate incident management process and reduce cost

  • GenAI recognizes patterns in data that may not be immediately apparent to humans
  • Enables continuous leaning and codification of subject matter expertise
  • GenAI quickly analyzes large datasets, provides recommendations in real-time
  • Delivers end-to-end incident resolution process automation
  • Reduces time and cost associated with root cause analysis and the determination of the right fix

Leading Network Operator uses VIA AIOps for Automated Incident Management

Transform Fault Management with Process Automation

  • Monitor and analyze syslog, trap, and alarms events from physical and virtual hosts within and across technology layers and applications in real-time
  • Enriches data through contextualization using machine-learned topologies and dimension discovery analysis 
  • Automatically generates baselines for every metric and dimension combination to detect faults more accurately 
  • Aggregates as appropriate multiple signals though process automation that may appear across service domains to a single incident 
  • Process automation powered by AI and machine learning defines probable root cause, symptoms and population impacted for rapid action and resolution 
  • Communicates bidirectionally with service management systems 

An Over-the-Top Video Service Provider Improves Customer Experience with VIA AIOps

Transform Performance Management with Process Automation

  • Monitor and analyze KPI time-series data from elements & applications
  • Unified data collection and analysis in cloud-native environments 
  • Cloud monitoring for performance across clusters vertically and horizontally without human intervention 
  • Detects service performance and customer-impacting incidents earlier with machine-learned baselines, machine-learned topologies, and stochastic modelling 
  • Eliminates multiple teams working on the same root cause through affinity analysis
  • Process automation defines root cause, symptoms and population impacted to enable faster action 
  • Prescribes next best action for incident remediation or prevention  

Top-Tier Cable Operator uses VIA Ops to reduce cost and improve DevOps and change assurance processes

Transfrom Change Assurance and Improve DevOps and CI/CD Processes

  • Discover dependencies with total ecosystem observability
  • Detect change to an entity’s attribute (e.g., subscriber’s device or element’s firmware)
  • Correlate alarms, events, incidents and change tickets
  • Monitor for and detect customer experience impact
  • Automate response with early anomaly detection resulting from change
  • Improves CI/CD Processes with the addition of AIOps 

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