Commodity Price Tracking
Transform decades of invoice data into procurement intelligence. Extract, classify, and analyse material and labour costs at scale.
Is there hidden value locked in your invoice archives?
Your finance systems hold years - maybe decades - of invoice data from across your supply chain. Within that dataset lies invaluable insight into price trends, regional variations, and procurement opportunities. But with millions of line items across thousands of suppliers, manual analysis is simply unfeasible. The business case for better procurement intelligence is clear; the path to extracting it has always been the blocker.
From invoice archives to actionable price intelligence
Line Item Extraction
Process thousands of invoices and extract individual line items automatically. Capture material descriptions, quantities, unit costs, supplier details, and dates - transforming unstructured invoice documents into structured, analysable data.
Taxonomy Classification
Classify extracted line items against your preferred taxonomy - Uniclass, NRM, or custom classification systems. Apply consistent categorisation across decades of invoices, enabling like-for-like comparison regardless of how different suppliers described the same materials.
High-Volume Processing
Scale to millions of line items without scaling your team. Deploy Hoppa Workbench in your own infrastructure to process invoice archives at speed - turning what would be years of manual work into a project measured in days or weeks.
Trend & Variance Analysis
Feed classified data to your finance and procurement teams for price sensitivity analysis. Identify regional price variations, track commodity trends over time, spot outlier invoices, and surface opportunities for contract renegotiation or bulk purchasing.
What this achieves
When you can see pricing patterns across your entire procurement history, negotiation becomes evidence-based. Identify suppliers charging above market rates. Spot commodities where bulk purchasing would deliver savings. Anticipate price movements based on historical trends. And if your dataset is large enough, you may find others willing to pay for access to your insights - turning a cost centre into a potential revenue stream.
Manual effort saved
100.0k hrs
Manual cost saved
£5.00m
Customer Stories
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