In a rapidly evolving technological landscape, downtime can be costly, leading to significant losses in revenue, productivity, and customer trust. Enter InsightFinder, a North Carolina-based startup that recently secured a $2 million seed investment to address this pressing issue using the power of machine learning. Founded by NC State University professor Helen Gu following 15 years of dedicated research, InsightFinder is poised to transform how businesses manage system monitoring and incident prevention.

A Proactive Approach to Monitoring

At its core, InsightFinder seeks to shift system monitoring from a reactive stance to a proactive one. Traditional monitoring solutions often focus on responding to alerts and issues as they arise, which can lead to a reactive cycle that doesn’t adequately safeguard against future incidents. Rami Essaid, the new Chief Operating Officer and former Distil Networks co-founder, emphasizes this transformation by stating, “We found that these problems happen to be repeatable, and the signals are there.” By leveraging artificial intelligence, InsightFinder processes these signals to predict system issues before they materialize, potentially preventing up to 50% of them proactively. This is a game-changer for businesses that can ill afford unexpected downtime.

Integrating with Existing Solutions

What sets InsightFinder apart from established players like Splunk, New Relic, and Datadog is its unique approach to aggregation. Rather than focusing on isolated components of a technology stack, InsightFinder acts as a comprehensive layer that interfaces with existing monitoring solutions. This not only reduces alert noise—a common frustration for IT teams—but also tracks issues across multiple alerts, enabling a seamless transition to automated issue resolution when possible. As Essaid notes, “It’s the only company that can actually take a lot of signals and use them to predict when something’s going to go bad.”

• Reduced Alert Fatigue: By filtering out unnecessary alerts, IT teams can focus on critical issues that truly require attention.
• Holistic Performance Insights: Aggregating data from various sources provides a well-rounded view of system health.
• Automation at Scale: The potential to automate responses to recurring issues saves time and resources.

Scaling into the Future

Currently, InsightFinder operates its software on-premises in ten large companies, but the startup has ambitious plans for a SaaS version to unlock access for a broader range of customers. With this round of investment, InsightFinder aims to establish a formal go-to-market strategy in 2020, enhancing its visibility and establishing partnerships that will facilitate growth. Their proven methodology, powered by machine intelligence, positions them uniquely in a competitive field.

Conclusion: The Future of Incident Management

InsightFinder’s journey from a research initiative to an emerging player in system monitoring exemplifies the intersection of academia and entrepreneurship, showcasing how rigorous research can lead to groundbreaking innovations. By tackling the critical issues of proactive incident management through AI, the company addresses a real need in the industry while fostering a culture of preparedness and responsiveness. As we move forward in an increasingly digital world, solutions like InsightFinder’s are not just beneficial—they’re essential.

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.