Cirries Technologies has announced the launch of its revolutionary solution, DART AI, for alert analysis and resolution. This is another step toward the company’s goal of enabling Autonomous Networks.
Cirries Technologies, a leader in network observability solutions, has announced the launch of its revolutionary solution, DART AI, for alert analysis and resolution. This is another step toward the company’s goal of enabling Autonomous Networks.
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Cirries Technologies has been developing network observability tools for nearly two decades. Coupled with the industry’s richest dataset and workflows that automatically analyze network issues, the integration of DART AI positions Cirries to provide the most comprehensive solution on the market.
“The integration of our network observability solution is a game-changer for the industry”, says Cody Martinson, COO of Cirries. “It sets a new standard, offering unmatched alert analysis and resolution using artificial intelligence. We believe this will pave the way for a new era of autonomous network management.”
Autonomous networks are advanced network systems that use artificial intelligence (AI) and machine learning (ML) to manage, optimize, and control network operations with minimal human intervention. “These networks are designed to be self-configuring, self-optimizing, self-healing, and self-protecting”, explains Martinson.
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Leveraging the robust and scalable infrastructure of DART AI, Cirries can now deliver precise accuracy and reliability in detecting and resolving network anomalies. Missed KPIs or network anomalies instigate an automated process that includes testing the problem area, collecting forensic data associated with the issue and forwarding this dataset to the trained AI models.
“It’s all about network excellence and reducing Mean Time to Repair (MTTR). Lower MTTR means quicker repair times, which means reduced downtime and increased productivity. Rapid resolution of issues is critical for customer satisfaction and trust for a service provider.” added Martinson.
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