Designed and trained account line prediction model for automated invoice processing. Project demonstrated technical limitations of pre-transformer architectures for variable-length sequence prediction.
Needed to predict variable-length list of account lines per invoice. Pre-transformer ML technology couldn't handle flexible-length predictions effectively. Management pressure to deliver despite technical constraints.
Clearly communicated technical limitations and feasibility constraints from project start. Designed and implemented single account line prediction as proof of concept. Trained and validated model over one year of development. Provided evidence-based recommendations for multi-line prediction requirements.
Project canceled due to fundamental limitation (single vs multiple line prediction). Correctly predicted technical constraints before development. Delivered working prototype within technical constraints. Demonstrated importance of technical feasibility assessment in AI projects.