Fine-Tuned AI Pipeline Converts 100,000+ Legacy Reports — Nearly One Million Records — into a 98%-Accurate Intelligence Layer
About the Client
As a global advisory firm with over 160 years of operating history, the client provides independent technical and risk advisory services to large industrial operators worldwide, helping them improve safety, performance, and sustainability.
- Industry: Technology
- Platforms: AI, Azure, Microsoft, Power Platform, and Python
The Challenge
The client maintained a repository of 100,000+ historical documents in SharePoint, accumulated over two decades of operations and stored in dozens of inconsistent formats, structures, and layouts — which led to multiple challenges:
- Identifying Relevant Reports: The 100,000+ files included duplicates, drafts, and irrelevant documents. Isolating valid, final reports by hand was not feasible at scale.
- Extracting Data Accurately: Reports varied in layout, file naming, date formats, and content organization, and many were incomplete. Off-the-shelf AI models produced error-prone, inconsistent outputs that couldn't support analytics or downstream decision-making.
- Processing Large and Complex Documents: Many reports spanned 200+ pages, in formats from scanned PDFs to Word and Excel — breaking standard processing methods and risking incomplete or failed extraction.
To address these challenges, the client required a solution that combined AI intelligence with governance mechanisms to automate document ingestion, standardization, and data extraction while ensuring accuracy and reliability for analytics and business use.
Our Solution
We delivered a cloud-native, AI-assisted document intelligence pipeline in 11 months — four tightly integrated phases — that ingested, fine-tuned, validated, and surfaced 100,000+ reports for analytics.
Intelligent Ingestion and Filtering
A cloud-based pipeline ingests documents in parallel from SharePoint at scale, with paginated processing that handles large file volumes without loss. Rule-based logic, structural patterns, and content categorization automatically isolate valid reports from duplicates, drafts, and irrelevant files.
AI-Assisted Extraction and Optimization
A Proof-of-Concept benchmarked candidate AI models on accuracy, performance, and security. The selected GPT model was fine-tuned under expert supervision on manually curated outputs, lifting the extraction score to 98%. Documents were classified as structured, semi-structured, or unstructured, and a domain-specific keyword dictionary plus enforced output schema kept results consistent even when source documents were incomplete.
Validation and Standardization
Specialists validated AI-generated data using deterministic rules, regex checks, and standardized naming conventions to enforce consistency across reports. PDF and Word content was converted to Markdown with layout preserved — improving both AI comprehension and downstream usability.
Scalable Processing and Analytics Enablement
Documents exceeding standard size limits were split for processing and merged post-extraction. Preprocessing ran independently to enable parallel execution at scale, and validated outputs flowed automatically into Power BI for reporting and analytics.
Technologies Used
The pipeline is built on Azure-native services for ingestion, AI extraction, storage, and analytics.
-
Azure Delta Storage
-
Azure Function
-
Azure Logic Apps
-
Azure OpenAI
-
Power BI
-
Azure Storage Table
-
Azure Synapse Analytics
-
Python
-
SharePoint
-
Terraform
Business Impact
The AI-assisted digitization pipeline turned 20 years of unstructured legacy reports into a searchable intelligence layer for internal decision-making, third-party data sharing, and regulatory reporting.
Processed 100,000+ documents across multiple formats at a 98% extraction score — turning two decades of raw reports into searchable, structured data
Turned a 20-year document archive into a live intelligence platform — powering internal decision-making, third-party data sharing, and regulatory reporting
How We Did It
-
Optimized Time Savings
by automatically identifying and sorting valid reports from a vast repository of irrelevant files and duplicate drafts.
-
Maximized Operational Efficiency
with AI-driven extraction and processing that delivered accurate, coherent, and comprehensive data.
-
Improved Decision Making and Monetization Potential
by turning processed data into insights that unlocked new commercial opportunities and revenue streams.
-
Facilitated Data Standardization
through uniform formatting of dates and key fields, along with new report templates defining mandatory and optional attributes.
-
Empowered Knowledge Transfer
by organizing data into a structured, searchable format that could be easily accessed.
-
Enhanced Scalability
with a parallel-processing pipeline on Azure that already absorbed 100,000+ documents and is built to elastically scale to any future document volume — with no ceiling on what the client can ingest next.
Other Case Studies
Enhanced VBA Logic–Based Excel Application Automates End-to-End Quotation Generation
Wine Manufacturer Redefines Reporting and Decision-Making Through a Reinforced ERP System
I wanted to take a moment to highlight and commemorate the efforts from our dedicated PIO team. To preface, the projects we work on here are complex, with rigid objectives, budgets, and timelines. Expectations are always high and are ever-changing. From the start of our relationship, the IO team was able to exceed expectations and make our business wishes a reality.
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.
I have been working with Programmers IO for more than 5 years now and I have been pleased with all projects and developers that I have worked with. We have had a few issues here and there but they have always fixed and made it right. They have been an excellent addition to our business.
Let’s Build Your AI-Readiness Roadmap Together
Contact us for a free strategy session with our experts.
Talk to an AI Expert
