For those who have spent years in the world of insurance, the industry is more than policies and claims — it is a deep, intricate ecosystem shaped by regulations, human judgment, and an unrelenting focus on risk management. But how do you convey this reality to a team of engineers and data scientists who have spent their careers optimizing algorithms rather than adjudicating claims? 

At DocLens.ai, an AI-powered complex claims management platform for P&C insurers, we face this challenge head-on. Our goal is not just to build cutting-edge AI solutions but to ensure that these solutions genuinely serve the needs of claims adjusters. That means turning highly skilled tech professionals into insurance problem-solvers. But this transformation is far from straightforward.   

The Blind Spots of Tech-first Thinking

The insurance industry operates in shades of gray, while technology often deals in black and white. One of the biggest challenges we have observed is that tech professionals, particularly those from a data science background, tend to view systems through a statistical lens.

If an AI model can correctly answer 90% of the questions, it is considered highly accurate. But in insurance, that one incorrect answer can be the most crucial piece of information — the one that impacts the final decision.

Take, for example, medical claims processing. A data scientist might focus on identifying all relevant medical events in a claim, ensuring high recall and precision. But for a claims adjuster, what truly matters is not just individual events but how a medical condition progresses over time. Has the claimant’s injury worsened? Have they shown signs of improvement? This insight transforms data into actionable intelligence. Without deep domain understanding, even the most sophisticated models can miss what matters most.

From Engineers to Insurance Problem-solvers

At DocLens.ai, we don’t expect our engineers to become insurance experts overnight. Instead, we embed insurance expertise into their everyday work. Our founding team includes industry and legal veterans with decades of experience in insurance. This ensures that every product discussion, every feature brainstorm, and every piece of software is informed by real-world insurance challenges.

One of our key strategies is fostering continuous interaction between engineers and claims adjusters. Rather than making assumptions about what the user needs, our engineers have direct access to insurance experts who guide them through the complexities of claims processing. 

We also encourage engineers to question every decision: Why does this feature matter to the adjuster? What impact will it have on their workflow? This practice not only sharpens their understanding of insurance but also leads to more effective, intuitive solutions.

When Engineers Gain Insurance Insights

The best innovations often emerge when engineers step into the shoes of insurance professionals. A prime example of this happened when we were working on medical event summarization. 

Initially, the team focused on extracting key medical events from claim documents — a seemingly straightforward AI task. However, through close collaboration with claims adjusters, we realized that a static list of events wasn’t enough. Adjusters needed to see the trajectory of a medical condition — whether it was improving or deteriorating — so they could make informed decisions. This insight led us to develop a feature that provides a chronological progression of medical conditions, making claims assessment significantly faster and more effective.

A Culture of Responsible AI

At DocLens.ai, we believe that building a strong AI-driven insurance platform is not just about technology. It’s about responsibility. Just as we build Responsible AI, we promote a responsible work culture where employees are encouraged to keep questioning, learning, and refining their understanding of insurance. We urge our team members to think beyond technology and focus on the end user’s decision-making process.

As Friedrich Nietzsche once said, “Those who have a 'Why' to live, can bear with almost any 'How'.” This philosophy underpins our approach. If our engineers understand why claims adjusters need a particular solution, they will figure out how to build it effectively.

The Road Ahead

We see this as a long-term journey. Creating insurance experts among tech professionals isn’t about overnight transformation. It’s a process built on real-world problem-solving. 

With continuous exposure to real claims challenges, our engineers are learning to think beyond code and understand the complexities that adjusters navigate daily. Over time, this approach not only strengthens the product but also empowers the tech team to make informed decisions on their own. While today’s focus is on complex claims, the ability to break down industry-specific problems and develop meaningful AI solutions will serve them well, no matter where technology takes them next.

At the heart of it all, our mission remains clear: we are not here to replace insurance experts. We are here to empower them. And that begins with making sure our engineers don’t just know tech — they understand insurance, too.