If you have used ChatGPT or Claude, you know they can type answers back to you. It’s like having a really smart assistant who can write essays, draft emails, or even code. But what if that assistant could do more than just talk? What if it could actually do things?
That’s where a newer kind of AI comes in. Instead of just generating text, these systems can perform actions. Think of it like upgrading from a calculator that just shows you the answer to one that can also place your grocery order. For businesses, especially those in complex fields like insurance, this shift from talking to doing is a really big deal.
Insurance brokerages, for example, are drowning in paperwork and repetitive tasks. Agents spend hours each week filling out forms, analyzing policies, and juggling data between different systems. With a global insurance industry worth $8 trillion, and facing a constant shortage of skilled workers, finding ways to work smarter, not just harder, is critical. Generic AI tools, the kind you might chat with, often fall short here. They don’t understand the intricate rules, the sensitive data, or the specific workflows that make insurance tick.
This is why companies like Cara are building specialized AI.
Why generic AI doesn’t cut it in insurance
Imagine trying to explain your company’s entire insurance process, all the forms, all the client nuances, all the carrier rules, to someone who has never worked in insurance before. That’s essentially what a generic AI has to do. It’s trained on a vast amount of general text and data, but it doesn’t inherently grasp the specific language, regulations, and workflows of a particular industry.
Insurance is a minefield of sensitive data – think personal financial details and health records. It’s also heavily regulated, meaning every step needs to be precise and auditable. A mistake can be costly, not just financially, but in terms of trust and compliance. Generic AI, while impressive for general tasks, often lacks the deep, domain-specific knowledge required to navigate these complexities safely and effectively. It’s like trying to use a general-purpose wrench to fix a specialized medical device; it might fit, but it’s not the right tool for the job.
Cara’s founders saw this problem firsthand. They previously ran a digital insurance brokerage that they successfully sold. During that time, they built an internal AI helper, a kind of copilot, powered by large language models (LLMs - these are the sophisticated AI models that power tools like ChatGPT). This copilot helped reduce how long things took, made data more accurate, and made life easier for their agents. The success of this internal tool led them to create Cara as a standalone product.
Cara’s AI: Built for the insurance world
Cara’s approach is different. They build AI that understands the insurance business from the ground up. This means the AI knows insurance jargon, understands policy structures, and can even handle requirements specific to different insurance carriers. It’s like hiring an experienced insurance underwriter who also happens to be an AI.
The system runs on Amazon Web Services (AWS), a cloud computing platform known for its reliability and security. Cara uses a few key AWS services to make its AI work.
First, there’s Amazon EKS (Elastic Kubernetes Service). Think of this as a highly organized manager for all of Cara’s different software pieces (called microservices). It makes sure these pieces work together smoothly, can handle lots of users at once – especially during busy periods like policy renewals – and keeps each brokerage’s data completely separate and secure. It’s like having a dedicated operations team for your AI, ensuring it scales and stays safe.
Then there’s Amazon Bedrock. This is where the AI magic happens. Amazon Bedrock gives Cara access to powerful foundation models (the advanced AI brains) through a simple, managed service. This means Cara doesn’t need to buy and maintain expensive, specialized computer hardware (like GPUs – Graphics Processing Units, which are chips originally designed for video games but now crucial for AI) just to run its AI. Cara can simply ask Bedrock to perform tasks, like analyzing coverage details or filling out forms, and get the results back.
Cara uses these foundation models for several crucial tasks:
- Coverage and quote intelligence: It can compare different insurance quotes, explain what’s covered, and point out any exclusions or gaps you might miss.
- Application and form automation: It can take information from existing documents and automatically fill out standard insurance forms, like ACORD forms, saving hours of manual data entry.
- Proposal and renewal generation: It can create professional, branded proposals and renewal documents for clients.
- Knowledge-driven workflows: It uses agency-specific rules, carrier preferences, and past deal information to guide agents’ decisions.
Security and speed, built-in
For insurance, security isn’t just a feature; it’s a requirement. Cara’s architecture on AWS is designed with this in mind. Each brokerage gets its own isolated environment. This means one brokerage’s sensitive client data is never mixed with another’s. It’s like having a private, secure office for each client within a larger, secure building. This isolation is vital for meeting strict industry regulations and providing a clear audit trail for every action.
Another big win is speed. Enterprise brokerages can get set up with Cara in a matter of hours, and they can start using custom AI workflows within days. Cara uses automated templates to quickly set up each new client’s isolated workspace, storage, and AI processing capabilities. This rapid deployment means businesses can start seeing the benefits of AI much faster than with traditional software implementations.
The infrastructure on AWS also ensures the system is always available and can handle sudden surges in demand. If thousands of agents are suddenly working on renewals, the system automatically scales up to meet that need.
Real results for brokerages
What does this all mean in practice? Cara’s AI is delivering measurable results for insurance brokerages.
- Time saved per user: Around 10 hours per week. This comes from automating tasks and making it faster to find the information agents need.
- Onboarding speed: Enterprise brokerages are onboarded in hours, and custom workflows go live in days.
- Concurrent capacity: The system supports thousands of concurrent users and workflows for each brokerage.
- Adoption: Cara is already used by hundreds of leading insurance agencies and brokerages.
These outcomes highlight how specialized AI, combined with a robust and secure cloud infrastructure, can transform operations. It’s about empowering insurance professionals to focus on what truly matters: building relationships with clients and managing risk, rather than getting bogged down in administrative work.
Vic Yeh, CEO of Cara, puts it well: “We are thrilled to advance the boundaries of domain-specific AI in real-world insurance use cases with AWS. Our goal is to help insurance professionals return to the core of our industry: the relationships.”
The insurance industry is still relatively early in its AI journey, but the potential is enormous. As demand for intelligent automation grows, Cara plans to expand its AI-driven workflows across all aspects of sales, servicing, and operations.
Cara’s story shows how AI can move beyond just chatting and become a powerful tool for doing work, especially when it’s built with a deep understanding of a specific industry’s needs.
To learn more about building AI applications on AWS, check out the AWS Architecture Center. You can get started with Amazon Bedrock by visiting Getting started with Amazon Bedrock. For Amazon EKS, see Getting started with Amazon EKS.
The Cara architecture uses Amazon EKS for orchestration and Amazon Bedrock for AI inference, ensuring isolated and scalable workspaces for brokerages.
Sources: aws.amazon.com