Loom Systems, the leading end-to-end AI-powered log analysis solution, today announced the release of its newest Streaming 2.0 platform, which enables more precise log analysis in Enterprise IT environments, ultimately reducing the manual work needed to optimize the product by up to 80%.
Loom Systems utilizes AI and machine learning in order to provide root cause analysis for issues across the IT stack, and provides IT professionals with recommendations for resolving problems before escalation. Loom’s solution changes the current paradigm of IT support, allowing companies to handle potential IT issues proactively, instead of once a problem has already occurred. This improves business productivity, alleviating the tedium of reading logs, and frees up time for operations to concentrate on other IT matters.
“We are very excited to introduce our Streaming 2.0 version,” said Gabby Menachem, CEO of Loom Systems. “Our latest update increases the level of precision of our AI technology, shortening the time to value, and enabling users to quickly and effectively produce meaningful insights from the vast amount of log data collected.”
Some additional features of Streaming 2.0 include:
New Data Architecture – every event streamed to Loom is mapped to a Source Type, which has all relevant information in order to analyze the event properly
Better Options to Structure Data – large organizations with complex infrastructures will benefit from improved usability and flexibility in structuring their data
Improved Integration with Notification Systems – enhanced email preferences
Additional Enhancements – script-less mapping of sources; custom alerts with almost no syntax required; more options for granular feedback for the machine learning engine
Loom Systems is a sponsor at this year’s AWS re:Invent 2017 conference, which runs from November 27 to December 1 in Las Vegas, Nevada, and will be demonstrating their AI-Powered Log Analysis solution at booth K10.