Loom Systems, today announced an AI-powered operational analytics platform used for real-time detection and resolution for any type of application. Targeted at DevOps and IT professionals, Loom instantly analyzes logs and semi-structured machine data for immediate visibility into a company’s digital environment. Accelerating the detection and resolution of IT problems in real-time, Loom helps reduce the cost and complexity of working with operational analytics. Via on-premises or SaaS installation, Loom Systems easily generates insights from raw data and with zero configuration or maintenance of the IT stack, including homegrown applications.
Digital transformation is augmenting every customer experience and has already become the dominant medium for growth in any business. According to a Gartner survey, rapid growth is expected to continue with 87 percent of businesses explicitly considering digital transformation in their capital allocation planning for the next two years. IT operations and application monitoring tools in the market today rely on manual work and deliver substandard customer experience for the digital era, creating a new market opportunity for advanced artificial intelligence (AI) tools to fill this gap with an automated, proactive approach.
“Many organizations implement log analysis solutions using manual techniques, however very few organizations derive the data’s full value from those efforts,” said John L Myers, managing research director, Enterprise Management Associates – a Boulder, CO based industry analysis firm. “Today’s transformation towards digital economy based on mobile and online apps requires an automated process that can extract insights out of the logs from complex IT environments. Loom Systems empowers organizations to make this leap by automatically loading, preparing and presenting application log data. This allows for real-time analytics as well as providing an intelligence layer that ties log data to corrective action.”
Loom Systems takes digitized information in structured, semi-structured or uncommonly structured text format and structures it automatically. By mathematically modeling how humans analyze such structures, Loom Systems fuses analytical skills with computational speed to simulate and enhance the entire data analysis cycle. The solution considers each metric and tracks it to learn its unique baseline and behavioral pattern over time to detect anomalies and predict future trends.
“Our previous analytics tool only reported issues happening in our digital systems after they had occurred,” said Greg Miller, IT director, RevTrak. “With Loom Systems our IT team can predict complex issues before they affect our business – critical to our operations and development teams. Furthermore, with Loom, we can now proactively problem solve in a few minutes only.”
Loom uses complex modules to determine whether a signal has shifted, as well as the type of shift that has occurred. The signal types are distinguished and anomaly detection algorithms are tailored to fit them. Signals are then automatically tracked in ways that complement their expected behavior.
Additional features and benefits of the Loom Systems platform include:
• Zero pre-processing required
• Detection of hidden and emerging issues in data and correlation of problems between all applications and services
• All data dynamically aggregated and correlated in real-time
• Automatic Root-cause Analysis
• Enrichment of alerts with insights and recommended resolutions from its Tribal Knowledge Bank, that contains a wide set of built-in recommended resolutions.
“At Loom Systems, we’ve built a platform to understand, reason and learn about constantly evolving digital environments and operational complexity,” said Gabby Menachem, founder and CEO, Loom Systems. “We build cognitive intelligence and expertise into a new set of tools that analyze logs, metrics and machine-generated data – just like DevOps application managers and IT professionals do every day – but with unprecedented speed and scale.”