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Case study

AI-powered automation of plot number extraction from insurance documents

180 minutes of manual work, down to 5 with AI. We built a system that extracts, validates, and delivers plot numbers from insurance documents straight into the client's environment – using OCR, the Polish language model Bielik, and a fully on-premise deployment.
  • Python
  • Docker
  • Kubernetes
  • MongoDB
  • RabbitMQ

About the Client

Our client is one of Poland's top insurance providers, with a long track record and a diverse product portfolio spanning multiple distribution channels. Their agricultural insurance line requires detailed land plot documentation – making it a prime candidate for process automation. The company actively embraces technology and AI-driven solutions to boost efficiency and elevate customer service.

Project location
Poland
Industry

Insurance

Sector
Private

Client’s challenges

Selling agricultural insurance through the agency channel meant agents had to manually key in plot numbers from client documents into the system – a painstaking process that took anywhere from 30 minutes to 3 hours, depending on the number of plots.

This manual approach was not only slow but error-prone, compromising quote accuracy and creating downstream issues in policy management. Worse still, it kept agents tied up with repetitive admin work instead of doing what they do best – advising clients and closing sales.

Without automation, the process simply didn't scale – particularly for clients with large numbers of land plots. The client needed a solution that would dramatically cut processing time, eliminate manual errors, and let agents refocus on high-value work. Crucially, any solution had to be deployed on-premise to meet strict data security requirements.

How did we support the client?

Nexio designed and delivered an end-to-end AI solution that fully automates plot number extraction from insurance documents. Built as a REST API using Python and FastAPI, the system combines OCR with Bielik – a Polish large language model – to intelligently extract and validate data.

The solution handles documents in a wide range of formats (PDF, JPG, PNG, GIF, TIFF, BMP, SVG, HEIC), automatically detecting and reading plot numbers from tables and structured listings. It also features a logo recognition mechanism that flags and rejects documents from competing insurers.

On the integration side, the system connects with the client's document repository and agent-facing application. Task queuing is handled by RabbitMQ, while MongoDB provides temporary data storage with automatic purging after 24 hours – ensuring full compliance with the client's data security policies.

The solution is fully containerized with Docker and runs on the client's Kubernetes clusters for scalability, high availability, and ease of management. Nexio owned the entire delivery lifecycle – from requirements analysis and architecture design through development, testing, and production rollout – while coordinating with other technology vendors to ensure seamless system-wide integration.

tech stack

  • Python
  • Docker
  • Kubernetes
  • MongoDB
  • RabbitMQ
  • Bielik.AI
  • PaddleOCR

Business benefits

  • Quote preparation time cut from up to 3 hours down to just 5 minutes by fully automating the extraction and entry of plot numbers into the system.
  • Manual transcription errors eliminated – AI-powered extraction and validation deliver cleaner data and more accurate quotes.
  • Agents freed from repetitive admin work, giving them more time to focus on what matters most – serving clients and closing sales.
  • Scalable handling of even the largest clients – the system processes hundreds of plot numbers in minutes, removing previous volume limitations.
  • Complete data security guaranteed by deploying the solution on-premise, fully aligned with the insurer's strict security policies.
  • Built-in document source verification – a logo recognition system automatically detects and rejects documents from competing insurers.

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