Client Overview
Curacel is an AI-powered insurance claims processor helping insurance providers automate and
streamline their operations. By integrating with insurers across multiple markets,
Curacel delivers faster, more accurate claims workflows which improves outcomes for both carriers and policyholders.
The Challenge
As Curacel rapidly expanded its insurance partnerships, its team was increasingly overwhelmed with the complexity
and volume of product and policy documentation. Each claim often required manual review of multiple files to
extract coverage details, leading to:
- Slower Processing Times due to time spent searching for policy terms
- Decreased Efficiency, pulling team members away from core decision-making and into mundane, manual tasks
- Higher Risk of Errors from misinterpreted or missed documentation, leading to potential inaccuracies in claim settlements
- Scalability Concerns as more insurers and product variations entered the system
Our Solution
Curacel partnered with Context Data to build a secure, scalable. comprehensive end-to-end solution leveraging a custom Retrieval-Augmented Generation (RAG) system.
- 01 - Custom Data Pipeline → We developed a robust data pipeline to seamlessly integrate and process product and policy documents from Curacel's various insurance partners.
This involved handling diverse document formats (PDF, Word, etc.), extracting key information, and organizing it into a unified knowledge base
- 02 - Central Vector Database → all data was transferred and stored centrally in a Vector Database
- 03 - Custom RAG application → We designed and implemented a bespoke RAG solution tailored to Curacel's specific needs, developing a sophisticated retrieval mechanism from the Vector Database.
- 04 - Intuitive Chatbot Interface → We built a custom and intuitive interface that allowed Curacel's team members to easily ask natural language questions
By transforming how internal teams access and interpret policy information, Context Data helped Curacel deliver on its promise of fast, intelligent claims processing without scaling headcount or manual effort.
This collaboration highlights how targeted, infrastructure-first AI solutions like RAG can unlock massive operational efficiency when deployed with intention, precision, and speed.
