All the interest around Enterprise AI has led many businesses to reevaluate their data architectures, as they understand that the true value of AI will be in the ability to drive deeper insights from their data. If businesses want to take full advantage of this transformative moment, they must quickly begin thinking about the ability to access and process all relevant data at ultra-low latencies, while ensuring data quality and security.
Businesses that don’t do this will not get the expected value from their AI projects. More importantly, such businesses not only risk the success of their AI projects, but also expose themselves to poor decision-making based on erroneous insights. This puts their corporate brand, their customer satisfaction and their financial success at risk.
Real-Time Is Not an Option; It’s an Eventuality
Think about your use cases – what happens if your portfolio risk profile and the associated hedging strategy is inaccurate; or if you send a promotion to a prospect at the wrong time, leading to your emails being banished to their spam folder; or if you miss an upward power spike in your energy grid and cannot adjust load on the grid in time? If you have errors in accurately processing these events, it will have significant implications on your business, whether it is not maintaining the necessary level of liquidity, losing a customer, or causing a power outage.
Anyone who thinks they do not need to process information or react to an event immediately is not looking far enough into their future. Every event eventually will have to be processed in real time, no matter what the enterprise or business does.
Creating the Right Data Foundation for AI
AI is becoming fully conversational, like a super-smart human with instantaneous access to massive amounts of relevant data. This will transform everything from software development, to sales, to customer service and support – so just about everything we do in businesses daily.
So how can businesses create the right data foundation for taking the best advantage of AI? By removing the primary obstacles to effectively using their data: data architecture complexity, slow data processing, and limited scalability. Instead, companies should focus on simplifying their data architecture to enable ultra-fast data processing while supporting massive data volumes.
At GridGain, we are singularly focused on making relevant data available to enterprises at ultra-low latencies with our unified real-time data platform. And we took this capability further by enabling high-performance execution of complex AI workloads to accelerate the decision-making process.
Take the next step in your AI strategy and join hundreds of successful GridGain customers in that journey.