Vortex is setting a new benchmark for customer experience in the IT industry. A Microsoft-only managed services provider, it redefines what small and medium-sized businesses expect from their IT partners by maximizing the value of their Microsoft licensing. With streamlined processes across Microsoft 365, Azure, Dynamics 365, and the Power Platform, Vortex builds environments that are secure, efficient and designed for growth. The story of Vortex began when President David Siegal and CTO Matt Wheeler asked a simple but powerful question—why should businesses settle for frustrating IT support? Organizations were weighed down by slow response times, disjointed services and providers who only acted after the problems escalated. Clients also shared the burden of re-explaining their systems on every call, working with technicians unfamiliar with their environment, and lacking proactive guidance. “We approach IT from a completely different angle to deliver a better end-user experience,” says Siegal. Instead of reacting to issues, Vortex focuses on preventing problems before they occur. It builds reliable systems, simplifies processes and ensures clients never feel like they are managing IT on their own. Maintaining more technicians per client than the competition, it ensures immediate access to expertise. Every call is answered directly by a local, full-time, Microsoft-certified professional who promptly resolves issues. Clients benefit from virtually zero call wait times and a 16-minute average email response, ensuring rapid support that eliminates frustration. The impact is clear from client stories. A Washington, D.C.-based government contractor struggled with VPN issues, firewall failures and unresponsive IT support, having endured years of poorly managed systems. Vortex stepped in to proactively manage the IT infrastructure and restore stability. C-level executives now regularly praise the seamless experience, describing Vortex as their “IT superheroes.” A nonprofit organization faced similar problems after relying on a copier company’s IT division. Tickets often took up to 48 hours to reach the right technician and some never received a response at all. Warranties had lapsed and infrastructure was unstable. The Vortex team stabilized their environment and closed long-standing gaps. During the first quarterly VCIO review, Vortex’s comprehensive network evaluation and 170-point report showed everything in excellent shape, proving that the nonprofit finally had a reliable partner. The client-first model has delivered results that speak volumes. In nearly six years of business, Vortex has maintained a 98.8 percent five-star review rate and a 100 percent client satisfaction rate, having never lost an MSP client to date. Every client remains willing to serve as a reference, a testament to the firm’s service excellence.

For years, engineering teams have struggled to fight back against rising cloud costs. But with countless resources that need attention, from AWS to Azure to Google Cloud, engineers just can’t keep up. The result is millions of dollars wasted, basically flushed down the drain. This was the problem that inspired Suresh Mathew to found Sedai. Today, Fortune 500 companies deploy Sedai’s platform to handle cloud cost optimization completely autonomously, without any manual effort. The platform has already performed over 25 million actions to optimize cloud resources, without ever causing an issue in production. So how did Sedai finally crack the code of cloud cost optimization? And what makes it safe? “Don’t make your engineers optimize cloud costs. This is a job that AI can do safely, right now,” says Mathew, founder and CEO. The Need for an Autonomous Cloud Cloud optimization looks simple, on the surface. For example, when an application requests more CPUs than it appears to use, the obvious solution is to scale down the CPUs to that level. Yet experienced engineers know that looks can be deceiving. This new configuration could degrade the app’s performance or even cause an outage, resulting in customer dissatisfaction. According to Mathew, there are too many variables for the manual approach to work; from internal changes, such as new feature releases, to external changes, like increased traffic. That’s why site reliability engineers (SRE) often over-provision resources on purpose. But with Sedai, companies no longer need to decide between cost and risk. “I spent a lot of my engineering career doing optimizations, so I know from experience that manual tuning is extremely boring and extremely risky,” Mathew said. “We built Sedai to evaluate every signal and metric from the cloud, every time it takes an action. To handle the complexity of the real world, you need to go autonomous.” Safety through Reinforcement Learning Built on patented machine learning models, Sedai’s platform continuously balances cost, performance and availability in real-time. This enables Sedai to perform intelligent optimizations that reduce cloud costs by as much as 50 percent, while also enhancing the safety and reliability of its customers’ environments.