Amazon’s New AI Models Revolutionize Claims Processing for Greater Efficiency

AI in Claims Processing

As artificial intelligence continues to evolve, many companies are exploring how it can help with complex and time-consuming tasks. One recent example comes from Amazon, which has introduced a new AI-based solution to improve how it handles internal claims processing. This may sound like a behind-the-scenes issue, but it’s actually quite important—especially for a company of Amazon’s size, where even small improvements in efficiency can have a big impact. With thousands of claims involving things like worker safety or delivery incidents, reviewing all the related documents quickly and fairly is no small task. That’s where Amazon’s new AI models come in.

Amazon’s Foundation Models

The core of this update is the use of two foundation models developed by Amazon: Nova Lite and Nova Micro. These models are part of the broader Amazon Nova family, designed to handle tasks like summarizing long documents or identifying key information from large datasets. In this case, the models are being used to read through and summarize claim-related documents—some of which can be tens of thousands of words long. The goal is to create short summaries that help risk managers understand each case more quickly without missing important details.

Improving Efficiency and Cost

Previously, Amazon had already built an AI-powered system to generate these summaries, but it faced challenges with speed and cost. Each claim could take several minutes to process, and as the number of claims grew, so did the computing costs. After testing various options, the team found that Nova Lite was able to cut processing time in half while reducing costs by 98%. Nova Micro performed even better in some cases—running four times faster at just 1% of the original cost. This kind of improvement makes it easier for teams to scale up their operations without sacrificing accuracy or performance.

How the System Works

The way this system works is also worth noting. First, raw data from claims is collected and stored using Amazon’s cloud services. Then, before any summarization happens, irrelevant parts are filtered out using an AI model based on Nova Lite. Only the most relevant information is passed along for summarization. This two-step approach helps reduce unnecessary processing and keeps costs down. The final summaries are then stored for easy access whenever new updates arrive for a claim.

Broader Context of AI Use

Looking at this development in context, it fits well with Amazon’s broader efforts over the past few years to apply AI internally—not just for customer-facing services but also for improving its own operations. In 2023 and 2024, we saw similar moves from Amazon using generative AI for fraud detection and financial analysis within its business units. The introduction of Nova Lite and Nova Micro continues that trend but focuses more on making foundational tools that other teams across Amazon can adopt easily.

Real-World Applications

What stands out here is not just the technology itself but how it’s being applied thoughtfully to real-world problems inside a large organization. Rather than chasing flashy applications, this project shows how AI can quietly improve everyday workflows—saving time and money while helping employees focus on higher-value work.

Conclusion on AI Adoption

In conclusion, Amazon’s use of its own Nova foundation models for internal claims processing highlights a practical side of AI adoption that often goes unnoticed. By focusing on cost-efficiency and speed without compromising quality, the company demonstrates how tailored solutions can make a meaningful difference at scale. For businesses handling large volumes of complex documents—or anyone interested in seeing how AI can support internal operations—this example offers a useful reference point for what thoughtful implementation looks like today.