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Logwise

Resolvd AI optimizes incident management by autonomously diagnosing and resolving system issues using a vast knowledge base.

Automation Updated 3 hours ago
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Logwise

Logwise's Top Features

AI/ML-driven log analysis
Real-time integration with Slack, Jira, and PagerDuty
Automated anomaly detection
Proactive alerting
Centralized data and log hub
Semantic search capabilities
Reduced alert noise
Accelerated incident response times
Comprehensive knowledge base creation
Automated insights for engineers

Frequently asked questions about Logwise

Resolvd is an AI-driven tool designed to handle on-call incidents by creating a knowledge base of logs, data sources, and applications to diagnose and resolve issues autonomously.

Resolvd reduces the time spent on manual log reviews by up to 80% through automated insights, allowing engineers to focus on resolving issues rather than sifting through data.

Yes, Resolvd ensures data security by adhering to industry-standard security practices and protocols to protect your data.

Resolvd offers various pricing plans to fit different organizational needs. It is best to book a demo to better understand which plan suits your requirements.

Yes, Resolvd can create alerts and employs automated anomaly detection to provide proactive alerting, thus minimizing alert noise.

Resolvd integrates with tools like Slack, Jira, and PagerDuty to surface log insights directly within your existing workflows.

Yes, Resolvd reduces alert noise by correlating events across various data sources to deliver relevant and critical alerts.

Key benefits include reducing time to response by 50%, returning hours to developers, and automating anomaly detection to spotlight critical issues.

Resolvd employs advanced AI/ML models to analyze log data and surface actionable insights, patterns, and anomalies.

You can book a demo to see how Resolvd works and understand its capabilities in enhancing your incident response strategy.

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Category
Automation
Tags
incident response
knowledge base
log analysis
AI/ML
log data
integration
real-time insights
alert noise reduction
incident response time
engineering focus

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