In an industry where every decision must be documented, justified and compliant, innovation is not a matter of speed; it’s a matter of trust. Claims handling is a prime example. Insurers face increasing pressure to process requests faster, with higher accuracy, while complying with complex regulatory frameworks. And yet, most claims departments are still drowning in manual work, incomplete information and disconnected systems.
This is where agentic AI is already making a difference.
At Dazerolab, we’ve been working on AI agents that don’t just talk or assist; they act. Claims-PRO, our AI agent designed to support high-volume claims processes, is one such example. In this article, let’s see together how agentic AI is rewriting the rules for claims management, and what that means for insurers and other regulated industries.
Let’s start with the fundamentals.
Why agentic AI, and why now?
Most people are familiar with generative AI: chat interfaces, content generation, document summaries. But agentic AI operates at a different level. It doesn’t just respond, it takes initiative. Given a task, an agent can define the steps needed, call external tools or APIs, interact with systems, and make decisions, all within a secure, observable, and auditable environment.
It’s the difference between asking for help and having a colleague who takes care of it.
In regulated sectors like insurance, that shift is critical. The real challenge isn’t just automation; it’s safe, explainable, policy-compliant automation. Agentic AI is purpose-built for this world: where rules must be followed, data must be protected, and every action must be traceable.
5 ways agentic AI transforms claim handling
But now, let’s go deep into the matter by seeing some real-world applications.
1. From inbox chaos to structured data
Every claim handler knows the pain: PDFs, emails, screenshots, hand-written notes. Evidence arrives in every format imaginable, and the first job is simply making sense of it.
An AI agent can automatically ingest claims files (even in bulk), extract relevant data, classify documents, and structure it in a way that downstream processes can use. No more scrolling through 12-page attachments to find one missing timestamp. No more data lost in translation between teams.
With document intelligence integrated from tools like Doc-PRO, agents gain the flexibility to deal with real-world complexity, them being scans, images, multilingual documents, and prepare a clean, usable dataset in seconds.
2. Real-time policy reasoning, not just lookup
In many insurance flows, the answer to a claim depends on policy terms, exclusions, customer history and specific thresholds. Checking all of this manually takes time, and often it ends up introducing inconsistencies.
Agentic AI can apply internal policies programmatically. It doesn’t just read conditions, it reasons with them. Based on the structured data from the claim, it matches against policy terms and verifies whether a claim is valid, partially covered, or out of scope. It flags borderline cases, explains its reasoning, and ensures that the same rules are applied to every claim, every time.
This is compliance by design, not as a final check, but baked into the decision-making process from step one.
3. Smart communication with customers and third parties
When documents are missing or verification is needed, communication with the claimant becomes critical. Generic emails or unclear requests delay the process and frustrate customers.
An agent can generate targeted, contextual requests: “We’ve reviewed your claim and need a confirmation of the original departure time, or a boarding pass. Please upload it here.” This saves time on both ends: the customer knows what’s needed, and the claim can move forward faster.
In parallel, agents can query third-party databases (e.g. flight data, public registries, internal fraud databases) to verify claims autonomously, without relying on the handler to chase down the information.
4. Human-in-the-loop decision support
AI doesn’t replace humans in regulated claims, it supports them. With the right setup, agentic AI can handle 80–90% of the work: from data extraction to verification, policy checks and proposal drafting.
But the final approval? That still belongs to a human.
This “human-in-the-loop” model ensures that sensitive or high-value claims get the oversight they need. The AI prepares the full case, complete with evidence, policy match, risk flags and proposed outcomes. The handler reviews, approves or adjusts, with full transparency on how the agent got there.
You don’t need to trust a black box. You can see how it thinks.
5. From pilot to production, without breaking everything
One of the biggest fears in AI transformation is integration. Teams worry: will we have to rebuild our stack? How long will it take? Can we even try it without involving every department?
With agentic AI, the answer is: start small, scale smart.
At Dazerolab, we deploy agents like Claims-PRO in real production environments with minimal disruption. Through modular orchestration, we define clear process flows, which tasks go to which agent, where human checks are required, and how the agent interacts with existing systems via APIs. We can work with snapshots of data (no live integration needed for pilots) and iterate fast.
That means a proof of concept can go live in weeks and be ready to scale in months.
Claims-PRO: an agent made for real-world insurance
Now, let’s talk about the tool behind the theory.
Claims-PRO is a purpose-built AI agent for processing insurance claims, starting with the travel sector and expanding into property, motor and health. It handles the full end-to-end process: intake, document parsing, verification, policy matching, external checks, and outcome proposal.
It’s multilingual. It handles messy evidence (images, scans, PDFs). It reasons with internal rules. And it integrates with your systems through our MCP interface (Model Context Protocol), which standardises the way agents access tools, databases and services.
What makes Claims-PRO unique is how it’s been built:
- It leverages Dazerolab’s Doc-PRO for advanced document understanding
- It uses multiple language models depending on the task (OpenAI, Mistral, Claude, etc.)
- It runs on a flow-based architecture that ensures compliance and modularity
- It’s engineered to scale, even for millions of claims per year
- It’s explainable, traceable, and GDPR-compliant from day one
Today, it’s already being tested with real clients, under real conditions, in full compliance with EU regulations. And we’re just getting started.
From POC to production: what you can expect
Deploying Claims-PRO doesn’t require a full system overhaul.
We typically begin with a focused POC: one type of claim, one process, with agreed KPIs. The agent is trained on real (but de-identified) data, connected to the necessary tools, and rolled out in a sandboxed environment. A human-in-the-loop reviews outcomes and validates the process.
Once results are stable, scaling is fast. You can add more flows, reduce human supervision where appropriate, and even move from travel to other lines of business. Our clients have seen time savings above 30%, reduced error rates, and improved customer satisfaction, all without adding headcount.
This is transformation you can measure.
What teams say when their new colleague is an AI agent
At first, there’s hesitation. A few curious team members become the pilot champions. Others are skeptical. Until they see the results.
Then comes the shift: what started as an experiment becomes the way things get done.
One of our clients in the energy sector saw this firsthand: once the team experienced how reliable the agent was and how much time it saved, adoption skyrocketed. We didn’t need to “evangelise” AI. The tool spoke for itself.
With Claims-PRO, we’ve designed for that moment. For that shift from “why should I use this?” to “how did I ever do without it?”
Agentic AI is not a trend. It’s infrastructure.
A recent report from MIT Boston noted that over 95% of generative AI experiments in enterprises didn’t deliver the expected value. Why? Because they focused on productivity at the individual level, not transformation at the organisational level.
Agentic AI does the opposite. It embeds into core processes. It doesn’t just generate; it operates. It’s not a shiny tool. It’s infrastructure for the next decade of work.
And in regulated industries, that infrastructure must be secure, explainable, and compliant by default. That’s exactly what we’re building at Dazerolab.
Ready to see it in action?
If you’re curious about bringing Claims-PRO into your organisation, or exploring how agentic AI could help in your case, we’d love to talk.
We offer ready-to-deploy POCs with:
- Minimal IT involvement
- Full data control (EU-based)
- Configurable human-in-the-loop
- Support for real-world documents and workflows
- Roadmap for production deployment
You can reach out directly on our LinkedIn page (make sure to follow us to keep up to date with all the news and new developments) or by writing us from our website.
Would you like to know more about Claims-PRO? Rewatch our LinkedIn live now (Italian language).