Enterprise IT Services & Cloud Transformation
United Kingdom
AI Engineer, Solutions Architect, BA, PM
4 months
The client specializes in providing cutting-edge technology consulting and managed services. Their solutions help organizations transition to modern IT architectures, improving data management, productivity, and operational efficiency.
Since the client’s data landscape included diverse sources: .xlsx, .csv, and scanned handwritten documents, – data cleaning, normalization, and transformation for business analytics were difficult. The scanned handwritten documents added further complexity, requiring manual extraction of embedded text and data points.
This manual work was error-prone, time-consuming, and inconsistent, with Python scripts needing constant adjustments to handle new data patterns and formats.
We implemented an AI agent for agentic document extraction based on LangChain and the OpenAI API, seamlessly integrated into the Azure environment. The goal was to automate and streamline data preparation with minimal manual intervention.
The AI-driven system automates data preparation through the following:
The agent reads and analyzes structured data from Excel and CSV files.
Leveraging OCR capabilities, the agent extracts both structured and unstructured content from from scanned hand-written documents.
It applies predefined normalization rules and automatically resolves data inconsistencies; all without requiring manual input.
To ensure seamless operation within existing infrastructure:
All AI operations are run within the client’s Azure environment, ensuring:
Within four months, the AI agent was fully deployed, greatly reducing the need for manual scripting and simplifying the entire data pipeline.
Now it automates data cleaning and normalization across various data sources, while also enabling accurate OCR data extraction process. As a result, the client experienced more consistent data, faster availability for analysis, and the ability to focus engineering efforts on high-value tasks.
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