Examples of how Volume's innovate approach accelerates how businesses navigate complex processes and data management
AI Data Extraction
Customer Context
A financial services organisation needed an automated way to process high volumes of German invoice documents, extracting key data and translating it into English for downstream use.
Volume Technology delivered an Al-powered solution for real-time ingestion, extraction, and translation-eliminating manual effort and improving accuracy at scale. Previously, teams had to read, translate, and rekey data from unstructured and inconsistent documents, creating high costs, delays, and errors. As volumes grew, this approach became unsustainable. The organisation required a scalable solution to extract, translate, and structure invoice data in real time.
Value Proposition
Volume transformed complex, multi-language invoice processing into a fully automated, real-time workflow-extracting, translating, and structuring data with speed, accuracy, and scale.
Required outcomes
- Automated extraction and translation of German invoice data into structured English outputs
- Significant reduction in manual processing and translation effort
- Improved speed, accuracy, and consistency of data capture
- Ability to process high volumes of documents in real time
Business Impact
- Eliminated manual document reading, translation, and rekeying
- Improved data quality and reliability across financial processes
- Enabled teams to focus on validation and decision-making rather than admin tasks
- Delivered a scalable document processing capability for multi-language inputs
- Increased operational efficiency while reducing cost and error rates
- Created trusted, usable data to support downstream workflows and reporting
Problems to be solved
- Manual reading, interpretation, and translation of German invoices into English
- High operational effort due to rekeying and human data entry
- Inconsistent document formats (scanned, unstructured, third-party inputs)
- Delays in processing impacting downstream financial operations
- Risk of errors and inconsistencies in extracted and translated data
- Limited ability to scale processing as document volumes increased