Sophie ingests any type of logs & metrics, structured and semi-structured, from any source. Our platform parses the logs, classifies them, and applies the proper measurement method to each property.
By leveraging advanced machine-learning algorithms, Sophie discovers patterns within the logs and learns their unique data behavior. Sophie sets dynamic thresholds based on the data signature in real-time to detect emerging issues at the very beginning and visualize them.
Sophie applies cognitive reasoning to detect cross-environment and cross-application issues, enabling you to gain full visibility of your digital environment, and provide you with the root-cause of problems in the most simple and comprehensive way.
Sophie enriches the detected events with insights written in plain English to explain what exactly happened, and recommends resolutions from its proprietary ever-growing knowledge base. Sophie empowers its users with the ability to share knowledge between the different tiers and save valuable tribal knowledge within the organization.
Sophie learns from your tickets, auto-correlates them to raw machine data in real-time and foresees future incidents. As an intelligent autonomous solution, Sophie will open tickets on key issues before your users do, enabling your team to become proactive and vastly reduce Mean Time to Detection.
Loom supports modern organizations to replace a broad range of IT operations processes and tasks, by connecting the dots between IT and business departments. To date, clients using Loom report a 93% alert noise reduction and 45% MTTR improvement in their daily IT Operations.