Court orders, receivables, and zero room for guesswork.
Even with mature infrastructure, EOS Group processes enormous volumes of structured and unstructured data originating from court orders and related enforcement packages. The business needed to modernize debt-collection operations while keeping extraction accuracy high enough to trust downstream receivables decisions.
Templated OCR and traditional RPA could not absorb the layout variance across jurisdictions—and any automation put in front of finance had to be defensible line by line to operations, audit, and compliance.
“Working with Ableneo to implement Kognitos’ automation solutions has been transformative for our unstructured document processing tasks. We’ve seen an impressive 98% success rate, allowing our team to focus on more strategic initiatives.”
- Process both structured tables and unstructured legal narratives
- Manage extraction, validation, and hand-offs without multiplying manual QC teams
- Improve receivables management workflows with transparent audit evidence
English as Code. Partner-led, production-proven.
Partnering with Ableneo
To accelerate delivery, EOS partnered with Ableneo—Slovakia’s pioneering IT consultancy for generative AI programs—and Kognitos to co-design governed automation that business and compliance stakeholders could follow line by line.
The joint team automated extraction of key facts from court orders and matched them with payment data so collectors could act faster with fewer swivel-chair steps. Success was defined up front: surpass a 60% straight-through accuracy threshold before declaring the model production-ready.
From a 60% target to 92% accuracy
The implemented solution cleared the production bar comfortably—reaching a 92% success rate on unstructured document processing—which gave finance leadership confidence to widen usage across additional receivables scenarios. Ableneo credited the partnership’s efficiency and reliability for helping EOS streamline operations faster than traditional IT-led automation programs typically allow.
