DigitalSprint transformed an outdated Oracle ATG Commerce platform into a scalable, cloud-native, microservice-based application, reducing licensing costs and improving agility. This modernization enabled faster releases and sustainable growth.
The value of making the right choice is clear. McKinsey reports that companies embedding AI across their operations are seeing profit improvements of up to 20%. Gartner projects that by 2026, over 80% of enterprises will have integrated AI into business processes, a sharp rise from just 10% in 2019. Yet these outcomes are not guaranteed. The real difference comes from whether businesses partner with someone who can bridge strategy, technology, and execution.
Every transformation journey begins with clarity. Some organizations aim to automate workflows to reduce costs, while others want AI to deliver predictive insights or personalize customer experiences. Without that clarity, projects risk becoming one-off experiments instead of sustainable change. At DigitalSprint, we spend time upfront helping businesses map their challenges against AI opportunities through discovery workshops. This ensures that the solutions we build — whether for automation, sales intelligence, or customer engagement — are tied directly to what matters most for the business.
Industry knowledge is equally vital. A healthcare provider has very different needs from a retail chain or a manufacturing company, and AI solutions must reflect those differences. Over the years, we’ve worked with clients in retail to build recommendation engines, with manufacturers to apply predictive analytics in supply chain forecasting, and with financial institutions to enhance fraud detection. Tailoring AI to industry realities makes the solutions immediately relevant and impactful.
Of course, no partnership is complete without innovation and scalability. AI is not just about algorithms; it’s about building systems that can evolve alongside technology and business needs. At DigitalSprint, our teams design solutions with this in mind. Conversational AI tools that improve customer interactions, predictive analytics platforms that empower decision-makers in real time, and cloud-native architectures that scale effortlessly — these are not future aspirations but solutions we are delivering today.
Industry knowledge is equally vital. A healthcare provider has very different needs from a retail chain or a manufacturing company, and AI solutions must reflect those differences. Over the years, we’ve worked with clients in retail to build recommendation engines, with manufacturers to apply predictive analytics in supply chain forecasting, and with financial institutions to enhance fraud detection. Tailoring AI to industry realities makes the solutions immediately relevant and impactful.