Analytics and monitoring are undergoing widespread change. We offer real-world use cases for how we can truly learn from machine learning today.

Forecasting business growth is not easy. In this post we cover several use cases that can help you on the path to achieving long-term growth and success.

The market shift in the monitoring space is happening quickly. A top-down data approach and auto-remediation with AI is what will help companies stay ahead in this ever-changing industry.

Predicting future demand for a company’s products or services is challenging. Anodot's ML-based Autonomous Forecast provides comprehensive autonomous forecasting of business growth and demand for organizations today.

What happened in July was one of many outages for Slack. In fact, the company lost $8 million in revenue last quarter after its platform went down for what accumulated to two hours in the course of 92 days.

Atlassian, the software company behind Jira and Trello, credits Anodot with keeping their employees in touch with product performance and customer experience.

What is customer experience monitoring? Why is it so difficult? Dive into this webinar with Customer Success Engineer, Steven Kirkpatrick, to better understand what it means to effectively monitor your user’s experience from start to finish.

This webinar gives a behind-the-scenes look at how Anodot uses its own product to monitor its customers’ health and engagement. More than 60% of tickets handled by Anodot’s support team are generated from monitoring alerts that notify us about real-time changes in our customer’s data rate and data usage. This immediacy allows our customer support team to take a proactive approach, as we often find issues before customers do.

In the first post of our three-part series on "Why anomaly detection is a business essential," we’re going to take a look at what constitutes an anomaly, what anomaly detection is, and how it could have a huge impact on business success.