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Building What’s Next: How Advarra Is Turning AI Into Meaningful Innovation

In clinical research, moving faster can’t mean lowering the bar. Advarra is evolving how software gets built—combining AI, context and human judgment to accelerate how ideas become value.

For Advarra, adopting AI isn’t simply a question of putting new tools in developers’ hands. It’s an opportunity to rethink how software gets built.

As AI becomes more capable, Advarra is applying the same rigor, expertise, and accountability that have long defined its role in clinical research to how it builds with AI—using technologies like Anthropic’s Claude to help teams move faster, learn earlier, and create more value.

It’s an approach Advarra is applying both to how its teams work and to the AI-enabled capabilities it is building for customers. AI adoption is a marathon rather than a sprint: an ongoing process of experimenting, learning, and adapting.

The philosophy is straightforward: use AI to supercharge people, not replace the judgment they bring.

The Bigger Shift Isn’t the Tool. It’s How You Build.

Early experiments with AI-assisted development surfaced an important lesson for Advarra: simply introducing AI into the existing software development lifecycle wasn’t enough.

The bigger opportunity was changing the way teams thought about the work itself.

Advarra began evolving its development practices around that idea—bringing business context into the process earlier, creating work that could be reviewed and validated in smaller increments, generating tests directly from acceptance criteria, and moving quality considerations earlier in the development cycle.

That evolution is part of a broader focus on context engineering: capturing the business, product, technical, and institutional context that makes Advarra unique, and making that context usable as AI technology continues to evolve.

The goal is bigger than developer productivity. It’s to create an approach that can adapt as AI evolves while preserving the data, expertise, and institutional knowledge that differentiate Advarra.

Bringing an Entrepreneurial Mindset to Enterprise Software

Working differently also means moving quickly enough to learn, with the rigor to scale responsibly.

Instead of spending long cycles defining a solution in isolation, teams can build enough to experience an idea, put it in front of the right people, learn from it, and adjust.

AI-assisted development with Claude can accelerate parts of the engineering lifecycle—from specification and development through testing and documentation—while Advarra’s teams remain accountable for what moves forward.

That balance matters. Advarra’s approach isn’t about removing human judgment from software development. It’s about creating more capacity for it: using AI where it can accelerate the work while keeping people responsible for the decisions, quality, and context that determine whether the work creates value.

Advarra has put this approach into practice with strategic partners, pairing its deep clinical research expertise, product vision, and customer understanding with specialized capabilities that can help accelerate its product roadmap and differentiation. Aditi is one of those partners, bringing AI and engineering expertise to help make ideas tangible, learn while building, and accelerate the path to value.

Brian Hart, Chief Technology Officer, Advarra
“Driving value for our customers is our North Star. We’re building an approach that brings together Advarra’s unique data and context, an architecture designed to adapt as technology changes, and strategic partners with specialized AI capabilities. That allows us to accelerate our product roadmap and bring meaningful innovation to market faster.”

— Brian Hart, CTO, Advarra

Making Innovation Tangible

One recent initiative put that model to the test.

Advarra identified an opportunity to make more value directly accessible to its customers. Rather than beginning with a long development cycle, the team focused first on creating something customers could experience and evaluate.

Within seven working days, Advarra and its end customer had a working experience they could interact with and use to validate the direction. From there, the team continued building, learning, and adjusting as the capability took shape.

Approximately six weeks later, that initial idea had developed into a working application.

More important than speed alone was what the initiative proved: Advarra could create a tighter path from idea to impact.

By bringing modern engineering, AI-assisted development with Anthropic’s Claude, and deep business context together from the start, Advarra could move quickly with its domain expertise, governance, and human judgment embedded in the way the work got done.

Building the Muscle

Context engineering isn’t a one-time skill. It’s a muscle Advarra is building across the portfolio.

For Advarra, this isn’t a one-time experiment or a race to adopt the latest technology. It’s a capability the organization is deliberately developing.

Across its portfolio, Advarra is learning where AI can amplify its teams, how development practices need to evolve around it, where new approaches work—and where they need to change.

The opportunity isn’t simply to build software faster, but to expand Advarra’s ability to turn ideas into meaningful advances for clinical research—combining the speed and leverage of AI with the expertise, judgment, and accountability the industry demands.

And Advarra is continuing to build that capability across its portfolio.

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