Applied Systems Innovation & Technology Culture

Applied Systems’ approach to innovation is grounded in a customer-first mindset, focusing on building technology that creates meaningful impact for both the insurance industry and the people it serves. Rather than innovating solely for growth, the company prioritizes solutions that solve real challenges, strengthen customer outcomes and drive long-term industry advancement.

“We want to win the right way, and that sets us apart. We aren’t developing products for our bottom line; we’re developing tools that will improve the industry and deliver results for our customers. We think that makes Applied Systems a really special place.”

On Applied Systems' embedding AI into product development and reducing time-consuming tasks:

"We can spend so much more time with customers because we don't have tickets or meetings or admin taking our time."

"Access to the tools sets the tone for the environment. When we use this in the right way, we can eliminate update meetings and roadblocks and enable everyone to go fast."

Where does AI show up in your stack? 

AI shows up across our development process, from helping us navigate complex codebases and document our work to supporting testing and accelerating how we move from an idea to a working solution. My own work spans front-end development, APIs, data and cloud-based services, so the value is much broader than generating code. AI can help connect context across those layers, while the engineer still owns the architecture, validation and decisions that determine whether the final product works for the customer.

How do you manage risk?

Speed matters, but so does building something people can depend on. One practice that has been especially valuable is test-driven development. By defining expected outcomes first, we can guide the model toward correct behavior, validate requirements earlier and identify edge cases before they become larger issues. We also review AI-assisted work, test the complete workflow and build safeguards directly into the product experience.

On my current project, we validate required information before a workflow can be scheduled and verify that the selected dataset can support the intended action. We also use feature flags as capabilities evolve and implement controls that limit what AI services can access, including restricting the tools and file types available to the model. AI helps us move faster, but responsibility for accuracy, security and reliability remains with the engineering team.

What’s an exciting project you’re on? 

I’ve been working on a new “Send Email” capability within Atlas data-driven workflows. The feature allows users to build email communications directly into an automated workflow by connecting a dataset, selecting approved templates and recipients from Epic, which is Applied’s agency management system, adding custom content, and using merge variables populated from their data.

One aspect I’m particularly proud of is the amount of validation built into the experience. The system verifies that required fields exist in the selected dataset, surfaces guidance when information is missing and supports users across multiple locales. The goal is to make it easier for customers to create personalized, data-driven communications while reducing the friction that can come with managing complex workflow configurations.

I owned the feature end to end, from concept planning and ticket creation to cross-team coordination, UI development, back-end API work and workflow logic. As someone still early in my career, being trusted with a project that spans so many parts of the stack has been an incredible opportunity to learn, contribute and see how product ideas become customer-facing capabilities.