Proxure
Case Study
Summary
- Client: Proxure
- Industry: Technology
- Challenges: Large volumes of invoices in multiple layouts, unstructured data buried in text, and an inefficient, manual extraction process.
- Ateko’s Solution: Built an automated PDF extraction tool leveraging Azure Document Intelligence (ADI) and Machine Learning models integrated with a high/low-confidence routing queue and an analytical dashboard.
- Results & Impact:
- Automated the extraction, classification, and structuring of complex invoice data.
- Reduced manual effort by routing low-confidence data to a manual review queue while auto-processing high-confidence data.
- Improved workforce productivity by shifting resources to higher-value analytical tasks.
Improving Data Operations
Empowering Procurement with Intelligent Document Extraction
Proxure’s transformation was driven by the vision to revolutionize professional services procurement, starting with the legal sector, by converting unstructured invoice data into actionable strategic insights.
The Challenge
Organizations frequently struggle to make strategic financial decisions regarding legal spending due to the sheer volume of invoices arriving in diverse layouts and from disparate sources. Valuable and critical data is often buried deep within unstructured text, such as line-item descriptions, terms, and conditions. For Proxure’s clients, extracting meaningful intelligence from these complex documents was too manual, slow, and inconsistent to process, creating operational friction.
The Solution
Proxure partnered with Ateko to build a PDF extraction tool powered by Azure Document Intelligence (ADI) and Machine Learning to automatically ingest, classify, structure, and visualize complex invoices.
Custom Model Training & Labeling
Using Azure Document Intelligence, sample PDFs were custom-labeled to identify and map the precise fields required for extraction. These machine learning models were iteratively trained and rigorously validated against testing datasets to ensure high accuracy before deployment.
Intelligent Inference & Exception Routing
To guarantee data integrity, Ateko built an Inference Model that evaluates incoming files and converts them into structured JSON. If the model determines it’s a high-confidence extraction, the data is pushed straight to the Bronze Data Lake. If low confidence is flagged, the document is routed to a manual review queue for validation.
Advanced Spend Analytics Dashboard
Once structured, the extracted invoice data is loaded into an interactive dashboard. This interface allows clients to easily explore, filter, and visualize their spending data, bringing previously hidden operational patterns to light.
Impact
The PDF extraction tool enabled Proxure’s clients to process invoices significantly faster and more cost-effectively, freeing teams up to focus on strategic analysis rather than manual data processes. Armed with deep visual insights into their data, their clients can now discover hidden spending trends, optimize their professional services budgets, and negotiate better rates with their vendors.
Join Colleen Pound (CEO & Co-founder, Proxure) and David Keith (SVP, Data & Cloud, Ateko) for an engaging fireside chat on the power of strategic tech partnerships.
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