AI-Powered ETL Pipeline
Designed and implemented an AI-powered ETL pipeline on Azure Databricks to automate document ingestion, transformation, and structured data processing.
Case Study
Databricks
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.
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.
The challenge
Newcleus managed high volumes of financial and insurance documents in multiple unstructured and semi-structured formats. Manual data extraction, inconsistent validation, and complex document processing resulted in reduced accuracy, operational inefficiencies, and slower reporting and decision-making.
The solution
Developed a scalable, AI-powered data platform that automated document extraction, transformed unstructured data into structured formats, validated data for accuracy, and streamlined processing across multiple document types. The solution improved operational efficiency, accelerated insights, and enabled faster, data-driven decision-making.
What we did
Web-Based Document Processing Interface
Built an intuitive web-based interface for document upload, workflow execution, and seamless automation of data processing tasks.
AI-Driven Data Extraction
Leveraged AI models to intelligently extract structured information from PDF documents with improved accuracy and consistency.
Medallion Data Architecture
Implemented a Bronze, Silver, and Gold Medallion architecture to automate data validation, transformation, and output generation in structured formats such as JSON and Excel.
Key Features
AI-Based Document Extraction
Leveraged AI models to extract structured data from complex PDF documents with high accuracy and minimal manual intervention.
Automated ETL Pipelines
Built end-to-end ETL workflows in Databricks to automate data ingestion, transformation, and processing at scale.
Medallion Architecture
Implemented a Bronze, Silver, and Gold data architecture to ensure reliable, scalable, and analytics-ready data processing.
Multi-Format Document Processing
Supported multiple document formats using configurable extraction patterns for flexible and efficient data processing.
Web-Based Workflow Interface
Developed an intuitive web interface for document uploads, automated processing triggers, and workflow management.
Data Validation & Quality Control
Applied automated validation rules and quality checks to ensure consistent, accurate, and reliable structured data outputs.
The
Impact
1
Operational Efficiency
Automated document processing significantly reduced manual effort, accelerated workflows, and shortened turnaround times.
2
Improved Data Accuracy
AI-powered data extraction minimized errors, ensured consistent outputs, and enhanced overall data quality.
3
Scalable Processing
A Databricks-powered architecture enabled efficient processing of large document volumes across diverse formats.
4
Faster Decision-Making
Structured, analytics-ready data accelerated reporting and delivered faster business insights for informed decisions.
5
Cost Optimization
Automation and optimized data workflows reduced operational costs while improving processing efficiency.