Quick Overview
ITI Foundation leveraged Microsoft’s Document Intelligence API to extract and structure data from large volumes of unstructured, non-standardized documents, creating a fully automated pipeline that enhanced data accessibility and analytics efficiency.
ITI Foundation
Company Size
~200 employees (estimated)
Revenue Range
Not publicly disclosed
Primary Challenge
Handling large volumes of unstructured and non-standardized documents across divisions causing inefficiencies
Key Metrics
\- Automated data extraction and classification\- Improved data accessibility and consistency\- Enhanced decision-making speed and accuracy
The Problem
Manual processing of diverse PDF documents was time-consuming and error-prone, limiting timely access to critical data.
The Solution
Implemented Microsoft Document Intelligence API to automate extraction, classification, and structuring of data from PDFs, enabling a streamlined data pipeline.
Results
\- Significant reduction in manual document processing time\- Improved data quality and accessibility\- Faster, more informed decision-making across divisions
“Microsoft AI tools have transformed how we handle complex document data, enabling faster and more accurate decisions.”
Details
Industry
Professional Services & Consulting
Departments
Data & Analytics
Use Cases
Document Management
Tags
Cost Reduction
AI Tools Used
No items found.
Sources
https://iti.ca/en/blog/artificial-intelligence/case-studies-getting-ready-for-artificial-intelligence/
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