PersoQua’s Document Automation Journey: 100 % Accuracy and Scalable Growth for Subsidy Management
We developed an end-to-end document information-extraction pipeline increasing the degree of automation while de-risking via human-in-the-loop gateways.
[CLIENT]
PersoQua, a leading Germany-based company, specializes in securing government subsidies for employee upskilling. Managing vast, sensitive client documents is a critical but challenging task. Manual sorting and data extraction are time-intensive, error-prone, and risk operational efficiency.
[CHALLENGE]
Scaling with the current process would require constant hiring for repetitive tasks, making growth inefficient and costly. A tailored solution is essential to streamline document processing, enhance accuracy, and free resources for higher-value work, ensuring lean, cost-effective, and sustainable growth.
[SOLUTION]
To tackle the challenges of manual document processing, a sophisticated end-to-end solution is being developed. The process starts by converting any document into an image format, enabling advanced Optical Character Recognition (OCR) to transform the content into text-based, machine-readable data. This provides a structured foundation for further analysis. Documents are first classified into categories such as CVs, pay slips, and ID cards. They are then clustered based on shared ownership, grouping documents belonging to the same individual across these categories. A custom human-in-the-loop system ensures the verification and confirmation of classifications and clusters, strategically minimising manual input while maximising processing throughput. Customer-specific information is extracted across document clusters, with the system visually highlighting data sources within the original documents for streamlined human verification. To further enhance efficiency, tailored business logic is implemented for data disambiguation, allowing full customisation of extractable fields and mechanisms. This approach significantly reduces human effort while maintaining accuracy and scalability.
[OUTCOME]
The solution delivered measurable business value, validated through a successful Proof of Concept (PoC) and further supported by ongoing collaboration with PersoQua. This strong partnership has fostered continuous refinement and development of the solution, bringing it closer to a robust production stage. Rigorous testing with an in-house benchmarking dataset demonstrated the effectiveness of the approach:
● Achieved 100% accuracy in both classification and clustering of documents.
● Covered 90% of data fields during extraction, with reliable identification and highlighting of documents requiring additional attention for missing information.
● Successfully identified missing client documents necessary to address critical gaps in the dataset.
The success of this PoC lays the groundwork for our continued collaboration, driving the next steps in PersoQua’s AI and automation journey.
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Ready to swap manual document chaos for 100 %‑accurate, AI‑driven efficiency?
Connect with us today to discover how our end‑to‑end automation can slash processing costs, ensure compliance, and free your team to focus on higher‑value work—all while scaling your subsidy programs with confidence.