In a recent interview, Ashok details the operational challenges that enterprises face and how their solutions address them effectively.
Transforming Business with Machine Learning and AI
We see machine learning and other AI techniques being applied to transform a wide variety of business processes. Software vendors are leveraging these technologies in business functions like CRM, HR, supply chain and procurement, and we’re noticing increasing use of AI within IT, particularly in IT operations and information security. At FogLogic, we began with a vision that AI should serve as a central ingredient in our solution, so we don’t have to add in that capability as a retrofit–and we expect to keep advancing our use of AI in the future. We also architected FogLogic as a cloud-based application as we believe the elastic nature of cloud processing and storage is really essential to fully leverage the potential of AI. Further, we wanted to ensure that we simplify implementation for our customers so they can be up and running the same day without having to hire consultants.
Empowering SAP Operations with Proactive AI
The companies we work with use SAP to run their core business processes and it’s imperative for their applications to run incident-free; they must also be able to resolve issues quickly.
What we don’t want to do is to create an incident alert for the user to look at unless it is meaningful. This is where the machine learning and AI comes into play
Simple and Intuitive Analysis
FogLogic collects, organizes and analyzes SAP application performance data in real-time, and uses AI in several ways. We profile the behavior of SAP systems by hour of day and day of week, looking for signs of abnormal behavior for that specific time window. While we highlight abnormal behavior as an anomaly, we don’t want to create incident alerts unless they are meaningful, so we analyze the anomalies and score them to determine their significance. We also compile detailed anomaly related analysis and develop what we call "curated insights." So when an incident does occur, most of the analysis work has been completed proactively and is delivered in a meaningful, actionable way so the user can start troubleshooting with a much higher level of insight into probable causes and isolate the actual root cause very quickly. The idea is for FogLogic to analyze the performance data, log messages and so on, and contextualize the information to narrow down the range of potential fixes so that users don’t have to start completely from scratch and figure out the root cause by themselves. This significantly minimizes the need for additional, time-consuming investigations, and an over reliance on specialist tribal knowledge.
Exemplary Success Stories
A large enterprise has relied on FogLogic for, among other things, “before and after” visibility and analysis. Prior to implementing any business process or changes to their SAP system, they use our analytics of their current environment to set goals for what they expect in terms of system performance after the change. After making the change, they’re able to see the effect of the change and how it compares to their earlier set up, and if it’s not what they hoped for, they have all the profiling, analysis and insights at their disposal to figure out what corrective action they should take. Doing this with legacy tools would have taken a considerable amount of time and resources. Another company has found that they’re able to troubleshoot incidents much faster using our platform. For P1 incidents, they were able to gather evidence of probable root cause identification in two hours and root cause isolation in a little over four hours, compared to their past norm of 10 days, which often resulted in them avoiding root cause analysis and then having to deal with repetitive incidents.
Strategy toward a Persistent Future
Our technology will grow and evolve along two dimensions. We will build on our powerful AI centric technology by bringing greater intelligence and analytics to drive towards customers’ goal of zero incidents. Second, we’ll broaden our market reach beyond SAP to cover other major enterprise applications.