Is manual loss-run processing slowing you down? Shepherd Insurance partnered with Pibit.ai for faster, more accurate loss run analysis.
Shepherd's OCR solution broke on even minor deviations in loss run format, and building a template for every variation was impractical, leaving underwriters back on manual data entry.
Download the full case study for the complete results table, integration path, and rollout sequence.
Download the full case studyPibit.ai's template-agnostic extraction combines LLMs, NLP and Computer Vision to read any loss run format, so underwriters get structured data on every submission without maintaining a single template.
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Pibit.AI increased our underwriting efficiency by processing every carrier format loss run seamlessly, including complex cases. A must for any MGAs.
Download the complete Shepherd case study for the results, implementation approach, and details on how Pibit fits into the underwriting workflow.
