AI-Driven Document Digitization Solution Transforms Nearly One Million Legacy Records into Actionable Insights
About the Client
This prominent consulting firm has been supporting various projects through expert technical services and solutions for over 160 years. They have assisted numerous companies across diverse sectors to enhance safety and drive sustainability.
- Industry: Technology
- Platforms: AI, Azure, Microsoft, Power Platform, and Python
The Challenge
The client struggled to:
- Filter critical reports from their SharePoint repository of nearly a million historical records, which also comprised duplicate entries, and other files.
- Standardize maritime reports with inconsistent naming conventions, file formats, and date patterns, many of which contained missing information and unstructured content.
- Process large reports exceeding 200 pages, which strained standard processing capabilities.
- Extract data from these reports using existing AI models. AI-generated results were often error-prone, incomplete, and inconsistent, leading to poor insights and impaired decision-making.
To address these challenges, the client sought an AI-driven, cloud-based document digitization solution that could automate the standardization, consolidation, and digitization of reports from various surveyors and transform this information into actionable insights.
Our Solution
We followed a multi-step, AI-powered approach to develop and deliver the required solution.
Logic App Pipeline Integration
A Logic App pipeline was developed to list all case folders from the client's SharePoint, process files in parallel, and handle subfolders and nested structures efficiently.
Pagination Settings Upgradation
The Logic App’s pagination settings were updated to expand the tool’s file-retrieval capacity from 100 to 5,000 files per folder while ensuring that no documents were skipped.
Azure Function Integration
A dedicated Azure Function was incorporated to handle pre-processing steps independently and resolve filename and path overrides during parallel processing.
Logic App Pipeline Modification
The newly developed Logic App pipeline was modified to filter valid reports by distinguishing relevant files from irrelevant ones using filename, content synonyms, and document structure pattern-based categorization.
Logic and Rules Implementation
Logic was implemented to differentiate drafts from final reports. Exclusion rules were enforced to detect and eliminate drafts while retaining the final version of each report.
Proof of Concept (PoC) Evaluation
A PoC was conducted to evaluate, identify, and select the most effective AI model that provided high data extraction accuracy, strong performance, and robust security.
Technologies Used
Using advanced tools and technologies, we delivered an intelligent solution within 11 months.
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Azure Delta Storage
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Azure Function
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Azure Logic Apps
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Azure OpenAI
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Power BI
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Azure Storage Table
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Azure Synapse Analytics
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Python
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SharePoint
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Terraform
Business Impact
Our smart solution helped automate report standardization, digitization, and transformation processes that drove measurable business benefits.
100% Successful Conversion of Unstructured Reports into Structured, Usable Data
100% Accurate Digitization Enabling Reporting, Analytics, and Actionable Insights
Here’s how we did it
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Optimized Time Savings
by automatically identifying and sorting valid reports from a vast repository of irrelevant files and duplicate drafts.
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Maximized Operational Efficiency
with AI-driven extraction and processing that delivered accurate, coherent, and comprehensive data.
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Improved Decision Making and Monetization Potential
through the transformation of processed data into actionable insights that helped unlock new opportunities and create additional revenue streams.
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Facilitated Data Standardization
through uniform formatting of dates and key fields, along with new report templates defining mandatory and optional attributes.
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Empowered Knowledge Transfer
by organizing data into a structured, searchable format that could be easily accessed.
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Enhanced Scalability
with a parallel-processing pipeline and cloud-based architecture capable of supporting future document volumes.
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Over the past year I have worked with them, they have worked very hard to understand our highly customized system and troubleshoot things with little or no documentation while managing to keep the business up and running normally. Without the hard work and dedication they have shown, I know we would have had some issues causing downtime or lost production. I am looking forward to continuing working them in the next year as well.
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