Databricks
Case Study
Intelligent Document Processing Platform
Data Template partnered with Newcleus to build an AI-driven data processing platform using Azure Databricks, enabling automated extraction and transformation of unstructured financial documents into analytics-ready data.
The Vision
To create a scalable, intelligent data platform that converts unstructured document data into structured formats, enabling faster insights, improved accuracy, and data-driven decision-making.
Scenario
Newcleus managed large volumes of financial and insurance documents in unstructured and semi-structured formats, leading to:
Manual and time-intensive data extraction
Inconsistent data quality and validation challenges
Multiple document formats increasing processing complexity
Delays in reporting and decision-making
What we did
Designed and implemented an AI-powered ETL pipeline on Azure Databricks
Built a web-based interface for document upload and workflow execution
Leveraged AI models for intelligent data extraction from PDF documents
Implemented Medallion architecture (Bronze, Silver, Gold) for structured data processing
Automated ingestion, transformation, validation, and output generation
Enabled conversion to structured formats such as JSON and Excel
Key features of the experience
The Impact
Transforming unstructured data into scalable, intelligent, and analytics-ready insights
Operational Efficiency
Automated document processing significantly reduced manual effort and turnaround time
Improved Data Accuracy
AI-driven extraction minimized errors and improved consistency of outputs.
Scalable Processing
Databricks-enabled architecture supports large volumes and diverse document types.
Faster Decision-Making
Enabled quicker reporting and insights through structured, ready-to-use data.
Cost Optimization
Reduced operational costs through automation and optimized data workflows.